Index of papers in Proc. ACL that mention
  • manually annotated
Lan, Man and Xu, Yu and Niu, Zhengyu
Experiments and Results
This is contrary to our original expectation that exp data which has been manually annotated for discourse connective disambiguation should outperform BLLIP which contains a lot of noise.
Experiments and Results
This finding indicates that under the multitask learning, it may not be worthy of using manually annotated corpus to generate auxiliary data.
Implementation Details of Multitask Learning Method
This is because the former data is manually annotated whether a word serves as discourse connective or not, while the latter does not manually disambiguate two types of ambiguity, i.e., whether a word serves as discourse connective or not, and the type of discourse relation if it is a discourse connective.
Introduction
To overcome the shortage of manually annotated training data, (Marcu and Echihabi, 2002) proposed a pattern-based approach to automatically generate training data from raw corpora.
Introduction
Later, with the release of manually annotated corpus, such as Penn Discourse Treebank 2.0 (PDTB) (Prasad et al., 2008), recent studies performed implicit discourse relation recognition on natural (i.e., genuine) implicit discourse data (Pitler et al., 2009) (Lin et al., 2009) (Wang et al., 2010) with the use of linguistically informed features and machine learning algorithms.
Introduction
2002) and (Sporleder and Lascarides, 2008), and (2) manually annotated explicit data with the removal of explicit discourse connectives.
Multitask Learning for Discourse Relation Prediction
Among them, it is manually annotated as an Expansion relation for 2, 938 times.
manually annotated is mentioned in 7 sentences in this paper.
Topics mentioned in this paper:
Kim, Jungi and Li, Jin-Ji and Lee, Jong-Hyeok
Experiment
Three human annotators who are fluent in the two languages manually annotated N-to-N sentence alignments for each language pairs (KR-EN, KR-CH, KR-JP).
Experiment
Manual Annotation and Agreement Study
Experiment
To assess the performance of our subjectivity analysis systems, the Korean sentence chunks were manually annotated by two native speakers of Korean with Subjective and Objective labels (Table l).
Multilanguage-Comparability 3.1 Motivation
Evaluating with intensity is not easy for the latter approach; if test corpora already exist with intensity annotations for both languages, normalizing the intensity scores to a comparable scale is necessary (yet is uncertain unless every pair is checked manually), otherwise every pair of multilingual texts needs a manual annotation with its relative order of intensity.
Related Work
(2008) and Boiy and Moens (2009) have created manually annotated gold standards in target languages and studied various feature selection and learning techniques in machine learning approaches to analyze sentiments in multilingual web documents.
manually annotated is mentioned in 7 sentences in this paper.
Topics mentioned in this paper:
Prabhakaran, Vinodkumar and Rambow, Owen
Data
We excluded a small subset of 419 threads that was used for previous manual annotation efforts, part of which was also used to train the DA and GDP taggers (Section 5) that generate features for our system.
Motivation
Another limitation of (Prabhakaran and Rambow, 2013) is that we used manual annotations for many of our features such as dialog acts and overt displays of power.
Motivation
Relying on manual annotations for features limited our analysis to a small subset of the Enron corpus, which has only 18 instances of hierarchical power.
Motivation
Like (Prabhakaran and Rambow, 2013), we use features to capture the dialog structure, but we use automatic taggers to generate them and assume no manual annotation at all at training or test time.
Structural Analysis
DIAPR: In (Prabhakaran and Rambow, 2013), we used dialog features derived from manual annotations — dialog acts (DA) and overt displays of power (ODP) — to model the structure of interactions within the message content.
Structural Analysis
In this work, we obtain DA and GDP tags on the entire corpus using automatic taggers trained on those manual annotations .
manually annotated is mentioned in 6 sentences in this paper.
Topics mentioned in this paper:
Wang, Mengqiu and Che, Wanxiang and Manning, Christopher D.
Bilingual NER Results
If a model only gives good performance with well-tuned hyper-parameters, then we must have manually annotated data for tuning, which would significantly reduce the applicability and portability of this method to other language pairs and tasks.
Introduction
Our method does not require any manual annotation of word alignments or named entities over the bilingual training data.
Joint Alignment and NER Decoding
On the other hand, the CRF—based NER models are trained on manually annotated data, and admit richer sequence and lexical features.
Related Work
proach is that training such a feature-rich model requires manually annotated bilingual NER data, which can be prohibitively expensive to generate.
Related Work
The model demonstrates performance improvements in both parsing and alignment, but shares the common limitations of other supervised work in that it requires manually annotated bilingual joint parsing and word alignment data.
manually annotated is mentioned in 5 sentences in this paper.
Topics mentioned in this paper:
Tang, Duyu and Wei, Furu and Yang, Nan and Zhou, Ming and Liu, Ting and Qin, Bing
Introduction
(2002) and employ machine learning algorithms to build classifiers from tweets with manually annotated sentiment polarity.
Introduction
We learn the sentiment-specific word embedding from tweets, leveraging massive tweets with emoticons as distant- supervised corpora without any manual annotations .
Introduction
0 We develop three neural networks to learn sentiment-specific word embedding (SSWE) from massive distant-supervised tweets without any manual annotations ;
Related Work
The sentiment classifier is built from tweets with manually annotated sentiment polarity.
Related Work
The reason is that RAE and NBSVM learn the representation of tweets from the small-scale manually annotated training set, which cannot well capture the comprehensive linguistic phenomenons of words.
manually annotated is mentioned in 5 sentences in this paper.
Topics mentioned in this paper:
Tomanek, Katrin and Hahn, Udo
Active Learning for Sequence Labeling
If Cflyj) exceeds a certain confidence threshold t, is assumed to be the correct label for this token and assigned to it.2 Otherwise, manual annotation of this token is required.
Experiments and Results
So, using SeSAL the complete corpus can be labeled with only a small fraction of it actually being manually annotated (MUC7: about 18 %, PENNBIOIE: about 13 %).
Introduction
In most annotation campaigns, the language material chosen for manual annotation is selected randomly from some reference corpus.
Introduction
In the AL paradigm, only examples of high training utility are selected for manual annotation in an iterative manner.
Summary and Discussion
Our experiments in the context of the NER scenario render evidence to the hypothesis that the proposed approach to semi-supervised AL (SeSAL) for sequence labeling indeed strongly reduces the amount of tokens to be manually annotated — in terms of numbers, about 60% compared to its fully supervised counterpart (FuSAL), and over 80% compared to a totally passive learning scheme based on random selection.
manually annotated is mentioned in 5 sentences in this paper.
Topics mentioned in this paper:
Cahill, Aoife and Riester, Arndt
Asymmetries in IS
In order to find out whether IS categories are unevenly distributed within German sentences we examine a corpus of German radio news bulletins that has been manually annotated for IS (496 annotated sentences in total) using the scheme of Riester (2008b).5
Discussion
(2007) present work on predicting the dative alternation in English using 14 features relating to information status which were manually annotated in their corpus.
Discussion
In our work, we manually annotate a small corpus in order to learn generalisations.
Discussion
From these we learn features that approximate the generalisations, enabling us to apply them to large amounts of unseen data without further manual annotation .
Syntactic IS Asymmetries
The problem, of course, is that we do not possess any reliable system of automatically assigning IS labels to unknown text and manual annotations are costly and time-consuming.
manually annotated is mentioned in 5 sentences in this paper.
Topics mentioned in this paper:
Webber, Bonnie
Abstract
All but the latter three were then characterised in terms of features manually annotated in the Penn Discourse TreeBank — discourse connectives and their senses.
Conclusion
It has characterised each genre in terms of features manually annotated in the Penn Discourse TreeBank, and used this to show that genre should be made a factor in automated sense labelling of discourse relations that are not explicitly marked.
The Penn Discourse TreeBank
Genre differences at the level of discourse in the PTB can be seen in the manual annotations of the Penn Discourse TreeBank (Prasad et al., 2008).
The Penn Discourse TreeBank
These have been manually annotated using the three-level sense hierarchy described in detail in (Miltsakaki et al., 2008).
manually annotated is mentioned in 4 sentences in this paper.
Topics mentioned in this paper:
duVerle, David and Prendinger, Helmut
Building a Discourse Parser
Both S and L classifiers are trained using manually annotated documents taken from the RST—DT corpus.
Building a Discourse Parser
In training mode, classification instances are built by parsing manually annotated trees from the RST—DT corpus paired with lexicalized syntax trees (LS Trees) for each sentence (see Sect.
Conclusions and Future Work
In this paper, we have shown that it is possible to build an accurate automatic text-level discourse parser based on supervised machine-learning algorithms, using a feature-driven approach and a manually annotated corpus.
Evaluation
A measure of our full system’s performance is realized by comparing structure and labeling of the RST tree produced by our algorithm to that obtained through manual annotation (our gold standard).
manually annotated is mentioned in 4 sentences in this paper.
Topics mentioned in this paper:
Severyn, Aliaksei and Moschitti, Alessandro and Uryupina, Olga and Plank, Barbara and Filippova, Katja
Abstract
An extensive empirical evaluation on our manually annotated YouTube comments corpus shows a high classification accuracy and highlights the benefits of structural models in a cross-domain setting.
Experiments
This is an important advantage of our structural approach, since we cannot realistically expect to obtain manual annotations for 10k+ comments for each (of many thousands) product domains present on YouTube.
Introduction
The second contribution of the paper is the creation and annotation (by an expert coder) of a comment corpus containing 35k manually labeled comments for two product YouTube domains: tablets and automobiles.1 It is the first manually annotated corpus that enables researchers to use supervised methods on YouTube for comment classification and opinion analysis.
YouTube comments corpus
For each video, we extracted all available comments (limited to maximum lk comments per video) and manually annotated each comment with its type and polarity.
manually annotated is mentioned in 4 sentences in this paper.
Topics mentioned in this paper:
Huang, Ruihong and Riloff, Ellen
Related Work
Nearly all semantic class taggers are trained using supervised learning with manually annotated data.
Related Work
Each annotator then labeled an additional 35 documents, which gave us a test set containing 100 manually annotated message board posts.
Related Work
With just fith of the training set, the system has about 1,600 message board posts to use for training, which yields a similar F score (roughly 61%) as the supervised baseline that used 100 manually annotated posts via 10-fold cross-validation.
manually annotated is mentioned in 4 sentences in this paper.
Topics mentioned in this paper:
Nakov, Preslav and Hearst, Marti A.
Relational Similarity Experiments
We further experimented with the SemEval’07 task 4 dataset (Girju et al., 2007), where each example consists of a sentence, a target semantic relation, two nominals to be judged on whether they are in that relation, manually annotated WordNet senses, and the Web query used to obtain the sentence:
Relational Similarity Experiments
The SemEval competition defines four types of systems, depending on whether the manually annotated WordNet senses and the Google query are used: A (WordNet=no, Query=no), B (WordNet=yes, Query=no), C (WordNet=no, Query=yes), and D (WordNet=yes, Query=yes).
Relational Similarity Experiments
We experimented with types A and C only since we believe that having the manually annotated WordNet sense keys is an unrealistic assumption for a real-world application.
manually annotated is mentioned in 4 sentences in this paper.
Topics mentioned in this paper:
Li, Linlin and Roth, Benjamin and Sporleder, Caroline
Experimental Setup
This dataset consists of 3964 instances of 17 potential English idioms which were manually annotated as literal or nonliteral.
Experiments
.‘he reason is that although this system is claimed 0 be unsupervised, and it performs better than .11 the participating systems (including the super-'ised systems) in the SemEval-2007 shared task, it till needs to incorporate a lot of prior knowledge, pecifically information about co-occurrences be-ween different word senses, which was obtained rom a number of resources (SSI+LKB) includ-ng: (i) SemCor (manually annotated); (ii) LDC-)SO (partly manually annotated ); (iii) collocation lictionaries which are then disambiguated semi-.utomatically.
Experiments
Even though the system is not 'trained”, it needs a lot of information which is argely dependent on manually annotated data, so t does not fit neatly into the categories Type II or Type III either.
Introduction
One major factor that makes WSD difficult is a relative lack of manually annotated corpora, which hampers the performance of supervised systems.
manually annotated is mentioned in 4 sentences in this paper.
Topics mentioned in this paper:
Laparra, Egoitz and Rigau, German
Conclusions and Future Work
That is, it can be applied where there is no available manual annotations to train.
Evaluation
Instead, the supervised approach would need a large amount of manual annotations for every predicate to be processed.
Introduction
However, current automatic systems require large amounts of manually annotated training data for each predicate.
Introduction
The effort required for this manual annotation explains the absence of generally applicable tools.
manually annotated is mentioned in 4 sentences in this paper.
Topics mentioned in this paper:
Kozhevnikov, Mikhail and Titov, Ivan
Conclusion
It allows one to quickly construct an SRL model for a new language without manual annotation or language-specific heuristics, provided an accurate model is available for one of the related languages along with a certain amount of parallel data for the two languages.
Evaluation
For English-French, the English CoNLL-ST dataset was used as a source and the model was evaluated on the manually annotated dataset from van der Plas et al.
Evaluation
Note that in case of French we evaluate against the output of a supervised system, since manual annotation is not available for this dataset.
Setup
Several approaches have been proposed to obtain an SRL model for a new language with little or no manual annotation .
manually annotated is mentioned in 4 sentences in this paper.
Topics mentioned in this paper:
Daxenberger, Johannes and Gurevych, Iryna
Abstract
We manually annotated a corpus of 636 corresponding and non-corresponding edit-turn-pairs.
Conclusion
To test this system, we manually annotated a corpus of corresponding and non-corresponding edit-turn-pairs.
Conclusion
With regard to future work, an extension of the manually annotated corpus is the most important issue.
Corpus
To assess the reliability of these annotations, one of the coauthors manually annotated a random subset of 100 edit-tum-pairs contained in ETP-gold as corresponding or non-corresponding.
manually annotated is mentioned in 4 sentences in this paper.
Topics mentioned in this paper:
Liu, Xiaohua and Zhou, Ming and Zhou, Xiangyang and Fu, Zhongyang and Wei, Furu
Abstract
We evaluate our method on a manually annotated data set, and show that our method outperforms the baseline that handles these two tasks separately, boosting the F1 from 80.2% to 83.6% for NER, and the Accuracy from 79.4% to 82.6% for NEN, respectively.
Conclusions and Future work
We evaluate our method on a manually annotated data set.
Experiments
We manually annotate a data set to evaluate our method.
Related Work
is trained on a manually annotated data set, which achieves an F1 of 81.48% on the test data set; Chiti-cariu et al.
manually annotated is mentioned in 4 sentences in this paper.
Topics mentioned in this paper:
Zhang, Meishan and Zhang, Yue and Che, Wanxiang and Liu, Ting
Introduction
Manually annotated corpora, such as the Chinese Treebank (CTB) (Xue et al., 2005), usually have words as the basic syntactic elements
Introduction
We manually annotate the structures of 37,382 words, which cover the entire CTB5.
Introduction
Luo (2003) exploited this advantage by adding flat word structures without manually annotation to CTB trees, and building a generative character-based parser.
Related Work
In addition, instead of using flat structures, we manually annotate hierarchal tree structures of Chinese words for converting word-based constituent trees into character-based constituent trees.
manually annotated is mentioned in 4 sentences in this paper.
Topics mentioned in this paper:
Kim, Seokhwan and Banchs, Rafael E. and Li, Haizhou
Evaluation
All the recorded dialogs with the total length of 21 hours were manually transcribed, then these transcribed dialogs with 19,651 utterances were manually annotated with the following nine topic categories: Opening, Closing, Itinerary, Accommodation, Attraction, Food, Transportation, Shopping, and Other.
Evaluation
For the linear kernel baseline, we used the following features: n-gram words, previous system actions, and current user acts which were manually annotated .
Evaluation
All the evaluations were done in fivefold cross validation to the manual annotations with two different metrics: one is accuracy of the predicted topic label for every turn, and the other is precisiorflrecall/F-measure for each event of topic transition occurred either in the answer or the predicted result.
manually annotated is mentioned in 3 sentences in this paper.
Topics mentioned in this paper:
Yu, Haonan and Siskind, Jeffrey Mark
Experiment
We manually annotated each video with several sentences that describe what occurs in that video.
Experiment
To evaluate our results, we manually annotated the correctness of each such pair.
Experiment
The scores are thresholded to decide hits, which together with the manual annotations , can generate TP, TN, FF, and FN counts.
manually annotated is mentioned in 3 sentences in this paper.
Topics mentioned in this paper:
Bansal, Mohit and Burkett, David and de Melo, Gerard and Klein, Dan
Introduction
Our model is also the first to directly learn relational patterns as part of the process of training an end-to-end taxonomic induction system, rather than using patterns that were hand-selected or learned via pairwise classifiers on manually annotated co-occurrence patterns.
Related Work
Both of these systems use a process that starts by finding basic level terms (leaves of the final taxonomy tree, typically) and then using relational patterns (hand-selected ones in the case of Kozareva and Hovy (2010), and ones learned separately by a pairwise classifier on manually annotated co-occurrence patterns for Navigli and Velardi (2010), Navigli et al.
Related Work
Our model also automatically learns relational patterns as a part of the taxonomic training phase, instead of relying on handpicked rules or pairwise classifiers on manually annotated co-occurrence patterns, and it is the first end-to-end (i.e., non-incremental) system to include heterogeneous relational information via sibling (e.g., coordination) patterns.
manually annotated is mentioned in 3 sentences in this paper.
Topics mentioned in this paper:
Chen, Yanping and Zheng, Qinghua and Zhang, Wei
Feature Construction
Head Noun: The head noun (or head mention) of entity mention is manually annotated .
Feature Construction
Third, the entity mentions are manually annotated .
Related Work
Disadvantages of the TRE systems are that the manually annotated corpus is required, which is time-consuming and costly in human labor.
manually annotated is mentioned in 3 sentences in this paper.
Topics mentioned in this paper:
Dong, Li and Wei, Furu and Tan, Chuanqi and Tang, Duyu and Zhou, Ming and Xu, Ke
Abstract
Furthermore, we introduce a manually annotated dataset for target-dependent Twitter sentiment analysis.
Experiments
After obtaining the tweets, we manually annotate the sentiment labels (negative, neutral, positive) for these targets.
Introduction
In addition, we introduce a manually annotated dataset, and conduct extensive experiments on it.
manually annotated is mentioned in 3 sentences in this paper.
Topics mentioned in this paper:
Hashimoto, Chikara and Torisawa, Kentaro and Kloetzer, Julien and Sano, Motoki and Varga, István and Oh, Jong-Hoon and Kidawara, Yutaka
Event Causality Extraction Method
We acquired 43,697 excitation templates by Hashimoto et al.’s method and the manual annotation of excitation template candidates.5 We applied the excitation filter to all 272,025,401 event causality candidates from the web and 132,528,706 remained.
Experiments
Note that some event causality candidates were not given excitation values for their templates, since some templates were acquired by manual annotation without Hashimoto et al.’s method.
Introduction
To make event causality self-contained, we wrote guidelines for manually annotating train-ing/development/test data.
manually annotated is mentioned in 3 sentences in this paper.
Topics mentioned in this paper:
Berg-Kirkpatrick, Taylor and Durrett, Greg and Klein, Dan
Experiments
To investigate the effects of using an in domain language model, we created a corpus composed of the manual annotations of all the documents in the Old Bailey proceedings, excluding those used in our test set.
Results and Analysis
We manually annotated the ink blotches (shown in red), and made them unobserved in the model.
Results and Analysis
We performed error analysis on our development set by randomly choosing 100 word errors from the WER alignment and manually annotating them with relevant features.
manually annotated is mentioned in 3 sentences in this paper.
Topics mentioned in this paper:
Zhu, Xiaodan and Guo, Hongyu and Mohammad, Saif and Kiritchenko, Svetlana
Experiment setup
Data As described earlier, the Stanford Sentiment Treebank (Socher et al., 2013) has manually annotated , real-valued sentiment values for all phrases in parse trees.
Experiment setup
The phrases at all tree nodes were manually annotated with one of 25 sentiment values that uniformly span between the positive and negative poles.
Introduction
The recently available Stanford Sentiment Treebank (Socher et al., 2013) renders manually annotated , real-valued sentiment scores for all phrases in parse trees.
manually annotated is mentioned in 3 sentences in this paper.
Topics mentioned in this paper:
McDonald, Ryan and Nivre, Joakim and Quirmbach-Brundage, Yvonne and Goldberg, Yoav and Das, Dipanjan and Ganchev, Kuzman and Hall, Keith and Petrov, Slav and Zhang, Hao and Täckström, Oscar and Bedini, Claudia and Bertomeu Castelló, Núria and Lee, Jungmee
Towards A Universal Treebank
The first is traditional manual annotation , as previously used by Helmreich et al.
Towards A Universal Treebank
2.2 Manual Annotation
Towards A Universal Treebank
Such a reduction may ultimately be necessary also in the case of dependency relations, but since most of our data sets were created through manual annotation , we could afford to retain a fine-grained analysis, knowing that it is always possible to map from finer to coarser distinctions, but not vice versa.4
manually annotated is mentioned in 3 sentences in this paper.
Topics mentioned in this paper:
Hartmann, Silvana and Gurevych, Iryna
FrameNet — Wiktionary Alignment
teas) independently on a manually annotated gold standard.
Related Work
In Tonelli and Pighin (2009), they use these features to train an SVM-classifier to identify valid alignments and report an Fl-score of 0.66 on a manually annotated gold standard.
Resource FNWKde
We compare FNWKde to two German frame-semantic resources, the manually annotated SALSA corpus (Burchardt et al., 2006) and a resource from Pado and Lapata (2005), henceforth P&L05.
manually annotated is mentioned in 3 sentences in this paper.
Topics mentioned in this paper:
Fader, Anthony and Zettlemoyer, Luke and Etzioni, Oren
Abstract
Given a large, community-authored, question-paraphrase corpus, we demonstrate that it is possible to learn a semantic lexicon and linear ranking function without manually annotating questions.
Introduction
These algorithms require no manual annotation and can be applied to large, noisy databases of relational triples.
Overview of the Approach
The final result is a scalable learning algorithm that requires no manual annotation of questions.
manually annotated is mentioned in 3 sentences in this paper.
Topics mentioned in this paper:
Andreevskaia, Alina and Bergler, Sabine
Factors Affecting System Performance
0 A balanced corpus of 800 manually annotated sentences extracted from 83 newspaper texts
Factors Affecting System Performance
200 sentences from this corpus (100 positive and 100 negative) were also randomly selected from the corpus for an inter-annotator agreement study and were manually annotated by two independent annotators.
Lexicon-Based Approach
In order to assign the membership score to each word, we did 58 system runs on unique nonintersecting seed lists drawn from manually annotated list of positive and negative adjectives from (Hatzivassiloglou and McKeown, 1997).
manually annotated is mentioned in 3 sentences in this paper.
Topics mentioned in this paper:
Li, Fangtao and Pan, Sinno Jialin and Jin, Ou and Yang, Qiang and Zhu, Xiaoyan
Introduction
However, the performance of these methods highly relies on manually annotated training data.
Introduction
However, these methods need to manually annotate a lot of training data in each domain.
Introduction
The sentiment and topic words are manually annotated .
manually annotated is mentioned in 3 sentences in this paper.
Topics mentioned in this paper:
Kim, Sungchul and Toutanova, Kristina and Yu, Hwanjo
Data and task
The approach uses a small amount of manually annotated article-pairs to train a document-level CRF model for parallel sentence extraction.
Data and task
Of these, we manually annotated 91 English-Bulgarian and 79 English-Korean sentence pairs with source and target named entities as well as word-alignment links among named entities in the two languages.
Data and task
At test time we use the local+global Wiki-based tagger to define the English entities and we don’t use the manually annotated alignments.
manually annotated is mentioned in 3 sentences in this paper.
Topics mentioned in this paper:
Kim, Seokhwan and Lee, Gary Geunbae
Evaluation
The experiments were performed on the manually annotated Korean test dataset.
Introduction
Several datasets that provide manual annotations of semantic relationships are available from MUC (Grishman and Sund-heim, 1996) and ACE (Doddington et al., 2004) projects, but these datasets contain labeled training examples in only a few major languages, including English, Chinese, and Arabic.
Introduction
Because manual annotation of semantic relations for such resource-poor languages is very expensive, we instead consider weakly supervised learning techniques (Riloff and Jones, 1999; Agichtein and Gravano, 2000; Zhang, 2004; Chen et al., 2006) to learn the relation extractors without significant annotation efforts.
manually annotated is mentioned in 3 sentences in this paper.
Topics mentioned in this paper:
Branavan, S.R.K. and Kushman, Nate and Lei, Tao and Barzilay, Regina
Experimental Setup
We also manually annotated the relations expressed in the text, identifying 94 of the Candidate Relations as valid.
Experimental Setup
Evaluation Metrics We use our manual annotations to evaluate the type-level accuracy of relation extraction.
Experimental Setup
The first, Manual Text, is a variant of our model which directly uses the links derived from manual annotations of preconditions in text.
manually annotated is mentioned in 3 sentences in this paper.
Topics mentioned in this paper:
LIU, Xiaohua and ZHANG, Shaodian and WEI, Furu and ZHOU, Ming
Experiments
In this section, we evaluate our method on a manually annotated data set and show that our system
Introduction
12,245 tweets are manually annotated as the test data set.
Related Work
A data set is manually annotated and a linear CRF model is trained, which achieves an F-score of 81.48% on their test data set; Downey et al.
manually annotated is mentioned in 3 sentences in this paper.
Topics mentioned in this paper:
Kummerfeld, Jonathan K. and Roesner, Jessika and Dawborn, Tim and Haggerty, James and Curran, James R. and Clark, Stephen
Conclusion
The result is an accurate and efficient wide-coverage CCG parser that can be easily adapted for NLP applications in new domains without manually annotating data.
Data
For supertagger evaluation, one thousand sentences were manually annotated with CCG lexical categories and POS tags.
Data
For parser evaluation, three hundred of these sentences were manually annotated with DepBank grammatical relations (King et al., 2003) in the style of Briscoe and Carroll (2006).
manually annotated is mentioned in 3 sentences in this paper.
Topics mentioned in this paper:
Feng, Yansong and Lapata, Mirella
Introduction
Obtaining training data in this setting does not require expensive manual annotation as many articles are published together with captioned images.
Related Work
The image parser is trained on a corpus, manually annotated with graphs representing image structure.
Related Work
Instead of relying on manual annotation or background ontological information we exploit a multimodal database of news articles, images, and their captions.
manually annotated is mentioned in 3 sentences in this paper.
Topics mentioned in this paper:
Cheung, Jackie Chi Kit and Penn, Gerald
Abstract
First, we show in a sentence ordering experiment that topological field information improves the entity grid model of Barzilay and Lapata (2008) more than grammatical role and simple clausal order information do, particularly when manual annotations of this information are not available.
Introduction
sentations to automatic extraction in the absence of manual annotations .
Introduction
Note, however, that the models based on automatic topological field annotations outperform even the grammatical role-based models using manual annotation (at marginal significance, p < 0.1).
manually annotated is mentioned in 3 sentences in this paper.
Topics mentioned in this paper:
Davidov, Dmitry and Rappoport, Ari
Introduction
Some of the teams have used the manually annotated WN labels provided with the dataset, and some have not.
Related Work
In this paper we do not use any manually annotated resources apart from the classification training set.
Related Work
This manually annotated dataset includes a representative rather than exhaustive list of 7 important nominal relationships.
manually annotated is mentioned in 3 sentences in this paper.
Topics mentioned in this paper: