pwc-archive/papers-with-abstracts huggingface dataset:
Data-Driven Metaphor Recognition and Explanation
Authors: Hongsong Li, Kenny Q. Zhu, Haixun Wang
Date: 2013-01-01 00:00:00
Proceeding: TACL 2013 1
Tasks: Reading Comprehension

Recognizing metaphors and identifying the source-target mappings is an important task as metaphorical text poses a big challenge for machine reading. To address this problem, we automatically acquire a metaphor knowledge base and an isA knowledge base from billions of web pages. Using the knowledge bases, we develop an inference mechanism to recognize and explain the metaphors in the text. To our knowledge, this is the first purely data-driven approach of probabilistic metaphor acquisition, recognition, and explanation. Our results shows that it significantly outperforms other state-of-the-art methods in recognizing and explaining metaphors.
Powergrading: a Clustering Approach to Amplify Human Effort for Short Answer Grading
Authors: Sumit Basu, Chuck Jacobs, V, Lucy erwende
Date: 2013-01-01 00:00:00
Proceeding: TACL 2013 1
Tasks: Clustering

We introduce a new approach to the machine-assisted grading of short answer questions. We follow past work in automated grading by first training a similarity metric between student responses, but then go on to use this metric to group responses into clusters and subclusters. The resulting groupings allow teachers to grade multiple responses with a single action, provide rich feedback to groups of similar answers, and discover modalities of misunderstanding among students; we refer to this amplification of grader effort as {``}powergrading.{''} We develop the means to further reduce teacher effort by automatically performing actions when an answer key is available. We show results in terms of grading progress with a small {``}budget{''} of human actions, both from our method and an LDA-based approach, on a test corpus of 10 questions answered by 698 respondents.
Training Deterministic Parsers with Non-Deterministic Oracles
Authors: Yoav Goldberg, Joakim Nivre
Date: 2013-01-01 00:00:00
Proceeding: TACL 2013 1
Tasks: ARC, valid

Greedy transition-based parsers are very fast but tend to suffer from error propagation. This problem is aggravated by the fact that they are normally trained using oracles that are deterministic and incomplete in the sense that they assume a unique canonical path through the transition system and are only valid as long as the parser does not stray from this path. In this paper, we give a general characterization of oracles that are nondeterministic and complete, present a method for deriving such oracles for transition systems that satisfy a property we call arc decomposition, and instantiate this method for three well-known transition systems from the literature. We say that these oracles are dynamic, because they allow us to dynamically explore alternative and nonoptimal paths during training {---} in contrast to oracles that statically assume a unique optimal path. Experimental evaluation on a wide range of data sets clearly shows that using dynamic oracles to train greedy parsers gives substantial improvements in accuracy. Moreover, this improvement comes at no cost in terms of efficiency, unlike other techniques like beam search.
Joint Morphological and Syntactic Analysis for Richly Inflected Languages
Authors: Bernd Bohnet, Joakim Nivre, Igor Boguslavsky, Rich{\'a}rd Farkas, Filip Ginter, Jan Haji{\v{c}}
Date: 2013-01-01 00:00:00
Proceeding: TACL 2013 1
Tasks: Dependency Parsing, Part-Of-Speech Tagging

Joint morphological and syntactic analysis has been proposed as a way of improving parsing accuracy for richly inflected languages. Starting from a transition-based model for joint part-of-speech tagging and dependency parsing, we explore different ways of integrating morphological features into the model. We also investigate the use of rule-based morphological analyzers to provide hard or soft lexical constraints and the use of word clusters to tackle the sparsity of lexical features. Evaluation on five morphologically rich languages (Czech, Finnish, German, Hungarian, and Russian) shows consistent improvements in both morphological and syntactic accuracy for joint prediction over a pipeline model, with further improvements thanks to lexical constraints and word clusters. The final results improve the state of the art in dependency parsing for all languages.
Measuring Machine Translation Errors in New Domains
Authors: Ann Irvine, John Morgan, Marine Carpuat, Hal Daum{\'e} III, Dragos Munteanu
Date: 2013-01-01 00:00:00
Proceeding: TACL 2013 1
Tasks: Articles, Domain Adaptation, Machine Translation, Translation

We develop two techniques for analyzing the effect of porting a machine translation system to a new domain. One is a macro-level analysis that measures how domain shift affects corpus-level evaluation; the second is a micro-level analysis for word-level errors. We apply these methods to understand what happens when a Parliament-trained phrase-based machine translation system is applied in four very different domains: news, medical texts, scientific articles and movie subtitles. We present quantitative and qualitative experiments that highlight opportunities for future research in domain adaptation for machine translation.
CLiPS Stylometry Investigation (CSI) corpus: A Dutch corpus for the detection of age, gender, personality, sentiment and deception in text
Authors: Ben Verhoeven, Walter Daelemans
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5
Tasks: Deception Detection, Text Classification

We present the CLiPS Stylometry Investigation (CSI) corpus, a new Dutch corpus containing reviews and essays written by university students. It is designed to serve multiple purposes: detection of age, gender, authorship, personality, sentiment, deception, topic and genre. Another major advantage is its planned yearly expansion with each year{'}s new students. The corpus currently contains about 305,000 tokens spread over 749 documents. The average review length is 128 tokens; the average essay length is 1126 tokens. The corpus will be made available on the CLiPS website (www.clips.uantwerpen.be/datasets) and can freely be used for academic research purposes. An initial deception detection experiment was performed on this data. Deception detection is the task of automatically classifying a text as being either truthful or deceptive, in our case by examining the writing style of the author. This task has never been investigated for Dutch before. We performed a supervised machine learning experiment using the SVM algorithm in a 10-fold cross-validation setup. The only features were the token unigrams present in the training data. Using this simple method, we reached a state-of-the-art F-score of 72.2{\%}.
On Paraphrase Identification Corpora
Authors: Vasile Rus, Rajendra Banjade, Mihai Lintean
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5
Tasks: Diversity, Natural Language Inference, Paraphrase Identification, Semantic Similarity, Semantic Textual Similarity

We analyze in this paper a number of data sets proposed over the last decade or so for the task of paraphrase identification. The goal of the analysis is to identify the advantages as well as shortcomings of the previously proposed data sets. Based on the analysis, we then make recommendations about how to improve the process of creating and using such data sets for evaluating in the future approaches to the task of paraphrase identification or the more general task of semantic similarity. The recommendations are meant to improve our understanding of what a paraphrase is, offer a more fair ground for comparing approaches, increase the diversity of actual linguistic phenomena that future data sets will cover, and offer ways to improve our understanding of the contributions of various modules or approaches proposed for solving the task of paraphrase identification or similar tasks.
A Corpus of Comparisons in Product Reviews
Authors: Wiltrud Kessler, Jonas Kuhn
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5
Tasks: Opinion Mining, Sentence, Sentiment Analysis

Sentiment analysis (or opinion mining) deals with the task of determining the polarity of an opinionated document or sentence. Users often express sentiment about one product by comparing it to a different product. In this work, we present a corpus of comparison sentences from English camera reviews. For our purposes we define a comparison to be any statement about the similarity or difference of two entities. For each sentence we have annotated detailed information about the comparisons it contains: The comparative predicate that expresses the comparison, the type of the comparison, the two entities that are being compared, and the aspect they are compared in. The results of our agreement study show that the decision whether a sentence contains a comparison is difficult to make even for trained human annotators. Once that decision is made, we can achieve consistent results for the very detailed annotations. In total, we have annotated 2108 comparisons in 1707 sentences from camera reviews which makes our corpus the largest resource currently available. The corpus and the annotation guidelines are publicly available on our website.
Generating and using probabilistic morphological resources for the biomedical domain
Authors: Vincent Claveau, Ewa Kijak
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5
Tasks: Information Retrieval, Machine Translation, Morphological Analysis

In most Indo-European languages, many biomedical terms are rich morphological structures composed of several constituents mainly originating from Greek or Latin. The interpretation of these compounds are keystones to access information. In this paper, we present morphological resources aiming at coping with these biomedical morphological compounds. Following previous work (Claveau et al. 2011,Claveau et al. 12), these resources are automatically built using Japanese terms in Kanjis as a pivot language and alignment techniques. We show how these alignment information can be used for segmenting compounds, attaching semantic interpretation to each part, proposing definitions (gloses) of the compounds... When possible, these tasks are compared with state-of-the-art tools, and the results show the interest of our automatically built probabilistic resources.
A System for Experiments with Dependency Parsers
Authors: Kiril Simov, Iliana Simova, Ginka Ivanova, Maria Mateva, Petya Osenova
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5
Tasks: Dependency Parsing, Sentence

In this paper we present a system for experimenting with combinations of dependency parsers. The system supports initial training of different parsing models, creation of parsebank(s) with these models, and different strategies for the construction of ensemble models aimed at improving the output of the individual models by voting. The system employs two algorithms for construction of dependency trees from several parses of the same sentence and several ways for ranking of the arcs in the resulting trees. We have performed experiments with state-of-the-art dependency parsers including MaltParser, MSTParser, TurboParser, and MATEParser, on the data from the Bulgarian treebank -- BulTreeBank. Our best result from these experiments is slightly better then the best result reported in the literature for this language.
Textual Emigration Analysis (TEA)
Authors: Andre Blessing, Jonas Kuhn
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5

We present a web-based application which is called TEA (Textual Emigration Analysis) as a showcase that applies textual analysis for the humanities. The TEA tool is used to transform raw text input into a graphical display of emigration source and target countries (under a global or an individual perspective). It provides emigration-related frequency information, and gives access to individual textual sources, which can be downloaded by the user. Our application is built on top of the CLARIN infrastructure which targets researchers of the humanities. In our scenario, we focus on historians, literary scientists, and other social scientists that are interested in the semantic interpretation of text. Our application processes a large set of documents to extract information about people who emigrated. The current implementation integrates two data sets: A data set from the Global Migrant Origin Database, which does not need additional processing, and a data set which was extracted from the German Wikipedia edition. The TEA tool can be accessed by using the following URL: http://clarin01.ims.uni-stuttgart.de/geovis/showcase.html
Phoneme Set Design Using English Speech Database by Japanese for Dialogue-Based English CALL Systems
Authors: Xiaoyun Wang, Jinsong Zhang, Masafumi Nishida, Seiichi Yamamoto
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5
Tasks: Language Modelling, Speech Recognition, Translation

This paper describes a method of generating a reduced phoneme set for dialogue-based computer assisted language learning (CALL)systems. We designed a reduced phoneme set consisting of classified phonemes more aligned with the learnersÂ’ speech characteristics than the canonical set of a target language. This reduced phoneme set provides an inherently more appropriate model for dealing with mispronunciation by second language speakers. In this study, we used a phonetic decision tree (PDT)-based top-down sequential splitting method to generate the reduced phoneme set and then applied this method to a translation-game type English CALL system for Japanese to determine its effectiveness. Experimental results showed that the proposed method improves the performance of recognizing non-native speech.
Toward a unifying model for Opinion, Sentiment and Emotion information extraction
Authors: Amel Fraisse, Patrick Paroubek
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5
Tasks: Opinion Mining, Sentiment Analysis

This paper presents a logical formalization of a set 20 semantic categories related to opinion, emotion and sentiment. Our formalization is based on the BDI model (Belief, Desire and Intetion) and constitues a first step toward a unifying model for subjective information extraction. The separability of the subjective classes that we propose was assessed both formally and on two subjective reference corpora.
Towards automatic quality assessment of component metadata
Authors: Thorsten Trippel, Daan Broeder, Matej Durco, Oddrun Ohren
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5

Measuring the quality of metadata is only possible by assessing the quality of the underlying schema and the metadata instance. We propose some factors that are measurable automatically for metadata according to the CMD framework, taking into account the variability of schemas that can be defined in this framework. The factors include among others the number of elements, the (re-)use of reusable components, the number of filled in elements. The resulting score can serve as an indicator of the overall quality of the CMD instance, used for feedback to metadata providers or to provide an overview of the overall quality of metadata within a reposi-tory. The score is independent of specific schemas and generalizable. An overall assessment of harvested metadata is provided in form of statistical summaries and the distribution, based on a corpus of harvested metadata. The score is implemented in XQuery and can be used in tools, editors and repositories.
PropBank: Semantics of New Predicate Types
Authors: Claire Bonial, Julia Bonn, Kathryn Conger, Jena D. Hwang, Martha Palmer
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5
Tasks: Abstract Meaning Representation, Machine Translation, Sentence

This research focuses on expanding PropBank, a corpus annotated with predicate argument structures, with new predicate types; namely, noun, adjective and complex predicates, such as Light Verb Constructions. This effort is in part inspired by a sister project to PropBank, the Abstract Meaning Representation project, which also attempts to capture who is doing what to whom in a sentence, but does so in a way that abstracts away from syntactic structures. For example, alternate realizations of a {`}destroying{'} event in the form of either the verb {`}destroy{'} or the noun {`}destruction{'} would receive the same Abstract Meaning Representation. In order for PropBank to reach the same level of coverage and continue to serve as the bedrock for Abstract Meaning Representation, predicate types other than verbs, which have previously gone without annotation, must be annotated. This research describes the challenges therein, including the development of new annotation practices that walk the line between abstracting away from language-particular syntactic facts to explore deeper semantics, and maintaining the connection between semantics and syntactic structures that has proven to be very valuable for PropBank as a corpus of training data for Natural Language Processing applications.
RESTful Annotation and Efficient Collaboration
Authors: Jonathan Wright
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5

As linguistic collection and annotation scale up and collaboration across sites increases, novel technologies are necessary to support projects. Recent events at LDC, namely the move to a web-based infrastructure, the formation of the Software Group, and our involvement in the NSF LAPPS Grid project, have converged on concerns of efficient collaboration. The underlying design of the Web, typically referred to as RESTful principles, is crucial for collaborative annotation, providing data and processing services, and participating in the Linked Data movement. This paper outlines recommendations that will facilitate such collaboration.
ALICO: a multimodal corpus for the study of active listening
Authors: Hendrik Buschmeier, Zofia Malisz, Joanna Skubisz, Marcin Wlodarczak, Ipke Wachsmuth, Stefan Kopp, Petra Wagner
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5

The Active Listening Corpus (ALICO) is a multimodal database of spontaneous dyadic conversations with diverse speech and gestural annotations of both dialogue partners. The annotations consist of short feedback expression transcription with corresponding communicative function interpretation as well as segmentation of interpausal units, words, rhythmic prominence intervals and vowel-to-vowel intervals. Additionally, ALICO contains head gesture annotation of both interlocutors. The corpus contributes to research on spontaneous human--human interaction, on functional relations between modalities, and timing variability in dialogue. It also provides data that differentiates between distracted and attentive listeners. We describe the main characteristics of the corpus and present the most important results obtained from analyses in recent years.
PoliTa: A multitagger for Polish
Authors: {\L}ukasz Kobyli{\'n}ski
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5
Tasks: Part-Of-Speech Tagging, POS, POS Tagging, Sentiment Analysis, Word Sense Disambiguation

Part-of-Speech (POS) tagging is a crucial task in Natural Language Processing (NLP). POS tags may be assigned to tokens in text manually, by trained linguists, or using algorithmic approaches. Particularly, in the case of annotated text corpora, the quantity of textual data makes it unfeasible to rely on manual tagging and automated methods are used extensively. The quality of such methods is of critical importance, as even 1{\%} tagger error rate results in introducing millions of errors in a corpus consisting of a billion tokens. In case of Polish several POS taggers have been proposed to date, but even the best of the taggers achieves an accuracy of ca. 93{\%}, as measured on the one million subcorpus of the National Corpus of Polish (NCP). As the task of tagging is an example of classification, in this article we introduce a new POS tagger for Polish, which is based on the idea of combining several classifiers to produce higher quality tagging results than using any of the taggers individually.
A Corpus of Participant Roles in Contentious Discussions
Authors: Siddharth Jain, Archna Bhatia, Angelique Rein, Eduard Hovy
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5
Tasks: Decision Making

The expansion of social roles is, nowadays, a fact due to the ability of users to interact, discuss, exchange ideas and opinions, and form social networks though social media. Users in online social environment play a variety of social roles. The concept of {``}social role{''} has long been used in social science describe the intersection of behavioural, meaningful, and structural attributes that emerge regularly in particular settings. In this paper, we present a new corpus for social roles in online contentious discussions. We explore various behavioural attributes such as stubbornness, sensibility, influence, and ignorance to create a model of social roles to distinguish among various social roles participants assume in such setup. We annotate discussions drawn from two different sets of corpora in order to ensure that our model of social roles and their signals hold up in general. We discuss the various criteria for deciding values for each behavioural attributes which define the roles.
Bilingual Dictionary Construction with Transliteration Filtering
Authors: John Richardson, Toshiaki Nakazawa, Sadao Kurohashi
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5
Tasks: Machine Translation, Translation, Transliteration

In this paper we present a bilingual transliteration lexicon of 170K Japanese-English technical terms in the scientific domain. Translation pairs are extracted by filtering a large list of transliteration candidates generated automatically from a phrase table trained on parallel corpora. Filtering uses a novel transliteration similarity measure based on a discriminative phrase-based machine translation approach. We demonstrate that the extracted dictionary is accurate and of high recall (F1 score 0.8). Our lexicon contains not only single words but also multi-word expressions, and is freely available. Our experiments focus on Katakana-English lexicon construction, however it would be possible to apply the proposed methods to transliteration extraction for a variety of language pairs.
Revising the annotation of a Broadcast News corpus: a linguistic approach
Authors: Vera Cabarr{\~a}o, Helena Moniz, Fern Batista, o, Ricardo Ribeiro, Nuno Mamede, Hugo Meinedo, Isabel Trancoso, Ana Isabel Mata, David Martins de Matos
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5
Tasks: speech-recognition, Speech Recognition

This paper presents a linguistic revision process of a speech corpus of Portuguese broadcast news focusing on metadata annotation for rich transcription, and reports on the impact of the new data on the performance for several modules. The main focus of the revision process consisted on annotating and revising structural metadata events, such as disfluencies and punctuation marks. The resultant revised data is now being extensively used, and was of extreme importance for improving the performance of several modules, especially the punctuation and capitalization modules, but also the speech recognition system, and all the subsequent modules. The resultant data has also been recently used in disfluency studies across domains.