pwc-archive/papers-with-abstracts huggingface dataset:
Croatian Memories
Authors: Arjan van Hessen, Franciska de Jong, Stef Scagliola, Tanja Petrovic
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5

In this contribution we describe a collection of approximately 400 video interviews recorded in the context of the project Croatian Memories (CroMe) with the objective of documenting personal war-related experiences. The value of this type of sources is threefold: they contain information that is missing in written sources, they can contribute to the process of reconciliation, and they provide a basis for reuse of data in disciplines with an interest in narrative data. The CroMe collection is not primarily designed as a linguistic corpus, but is the result of an archival effort to collect so-called oral history data. For researchers in the fields of natural language processing and speech analy{\^A}{\neg}sis this type of life-stories may function as an object trouv{\'e} containing real-life language data that can prove to be useful for the purpose of modelling specific aspects of human expression and communication.
Combining elicited imitation and fluency features for oral proficiency measurement
Authors: Deryle Lonsdale, Carl Christensen
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5
Tasks: Language Modelling

The automatic grading of oral language tests has been the subject of much research in recent years. Several obstacles lie in the way of achieving this goal. Recent work suggests a testing technique called elicited imitation (EI) that can serve to accurately approximate global oral proficiency. This testing methodology, however, does not incorporate some fundamental aspects of language, such as fluency. Other work has suggested another testing technique, simulated speech (SS), as a supplement or an alternative to EI that can provide automated fluency metrics. In this work, we investigate a combination of fluency features extracted from SS tests and EI test scores as a means to more accurately predict oral language proficiency. Using machine learning and statistical modeling, we identify which features automatically extracted from SS tests best predicted hand-scored SS test results, and demonstrate the benefit of adding EI scores to these models. Results indicate that the combination of EI and fluency features do indeed more effectively predict hand-scored SS test scores. We finally discuss implications of this work for future automated oral testing scenarios.
Semantic Search in Documents Enriched by LOD-based Annotations
Authors: Pavel Smrz, Jan Kouril
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5
Tasks: Information Retrieval, Retrieval, Semantic Retrieval

This paper deals with information retrieval on semantically enriched web-scale document collections. It particularly focuses on web-crawled content in which mentions of entities appearing in Freebase, DBpedia and other Linked Open Data resources have been identified. A special attention is paid to indexing structures and advanced query mechanisms that have been employed into a new semantic retrieval system. Scalability features are discussed together with performance statistics and results of experimental evaluation of presented approaches. Examples given to demonstrate key features of the developed solution correspond to the cultural heritage domain in which the results of our work have been primarily applied.
A Meta-data Driven Platform for Semi-automatic Configuration of Ontology Mediators
Authors: Manuel Fiorelli, Maria Teresa Pazienza, Arm Stellato, o
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5

Ontology mediators often demand extensive configuration, or even the adaptation of the input ontologies for remedying unsupported modeling patterns. In this paper we propose MAPLE (MAPping Architecture based on Linguistic Evidences), an architecture and software platform that semi-automatically solves this configuration problem, by reasoning on metadata about the linguistic expressivity of the input ontologies, the available mediators and other components relevant to the mediation task. In our methodology mediators should access the input ontologies through uniform interfaces abstracting many low-level details, while depending on generic third-party linguistic resources providing external information. Given a pair of ontologies to reconcile, MAPLE ranks the available mediators according to their ability to exploit most of the input ontologies content, while coping with the exhibited degree of linguistic heterogeneity. MAPLE provides the chosen mediator with concrete linguistic resources and suitable implementations of the required interfaces. The resulting mediators are more robust, as they are isolated from many low-level issues, and their applicability and performance may increase over time as new and better resources and other components are made available. To sustain this trend, we foresee the use of the Web as a large scale repository.
Semantic approaches to software component retrieval with English queries
Authors: Huijing Deng, Grzegorz Chrupa{\l}a
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5
Tasks: Code Search, Language Modelling, Machine Translation, Retrieval

Enabling code reuse is an important goal in software engineering, and it depends crucially on effective code search interfaces. We propose to ground word meanings in source code and use such language-code mappings in order to enable a search engine for programming library code where users can pose queries in English. We exploit the fact that there are large programming language libraries which are documented both via formally specified function or method signatures as well as descriptions written in natural language. Automatically learned associations between words in descriptions and items in signatures allows us to use queries formulated in English to retrieve methods which are not documented via natural language descriptions, only based on their signatures. We show that the rankings returned by our model substantially outperforms a strong term-matching baseline.
The Ellogon Pattern Engine: Context-free Grammars over Annotations
Authors: Georgios Petasis
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5
Tasks: Named Entity Recognition (NER), Sentiment Analysis

This paper presents the pattern engine that is offered by the Ellogon language engineering platform. This pattern engine allows the application of context-free grammars over annotations, which are metadata generated during the processing of documents by natural language tools. In addition, grammar development is aided by a graphical grammar editor, giving grammar authors the capability to test and debug grammars.
Missed opportunities in translation memory matching
Authors: Friedel Wolff, Laurette Pretorius, Paul Buitelaar
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5
Tasks: Information Retrieval, Machine Translation, text similarity, Translation

A translation memory system stores a data set of source-target pairs of translations. It attempts to respond to a query in the source language with a useful target text from the data set to assist a human translator. Such systems estimate the usefulness of a target text suggestion according to the similarity of its associated source text to the source text query. This study analyses two data sets in two language pairs each to find highly similar target texts, which would be useful mutual suggestions. We further investigate which of these useful suggestions can not be selected through source text similarity, and we do a thorough analysis of these cases to categorise and quantify them. This analysis provides insight into areas where the recall of translation memory systems can be improved. Specifically, source texts with an omission, and semantically very similar source texts are some of the more frequent cases with useful target text suggestions that are not selected with the baseline approach of simple edit distance between the source texts.
Universal Stanford dependencies: A cross-linguistic typology
Authors: Marie-Catherine de Marneffe, Timothy Dozat, Natalia Silveira, Katri Haverinen, Filip Ginter, Joakim Nivre, Christopher D. Manning
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5

Revisiting the now de facto standard Stanford dependency representation, we propose an improved taxonomy to capture grammatical relations across languages, including morphologically rich ones. We suggest a two-layered taxonomy: a set of broadly attested universal grammatical relations, to which language-specific relations can be added. We emphasize the lexicalist stance of the Stanford Dependencies, which leads to a particular, partially new treatment of compounding, prepositions, and morphology. We show how existing dependency schemes for several languages map onto the universal taxonomy proposed here and close with consideration of practical implications of dependency representation choices for NLP applications, in particular parsing.
Collaboratively Annotating Multilingual Parallel Corpora in the Biomedical Domain---some MANTRAs
Authors: Johannes Hellrich, Simon Clematide, Udo Hahn, Dietrich Rebholz-Schuhmann
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5
Tasks: Named Entity Recognition (NER), Translation

The coverage of multilingual biomedical resources is high for the English language, yet sparse for non-English languagesâ€•an observation which holds for seemingly well-resourced, yet still dramatically low-resourced ones such as Spanish, French or German but even more so for really under-resourced ones such as Dutch. We here present experimental results for automatically annotating parallel corpora and simultaneously acquiring new biomedical terminology for these under-resourced non-English languages on the basis of two types of language resources, namely parallel corpora (i.e. full translation equivalents at the document unit level) and (admittedly deficient) multilingual biomedical terminologies, with English as their anchor language. We automatically annotate these parallel corpora with biomedical named entities by an ensemble of named entity taggers and harmonize non-identical annotations the outcome of which is a so-called silver standard corpus. We conclude with an empirical assessment of this approach to automatically identify both known and new terms in multilingual corpora.
On the Importance of Text Analysis for Stock Price Prediction
Authors: Heeyoung Lee, Mihai Surdeanu, Bill MacCartney, Dan Jurafsky
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5
Tasks: Prediction, Stock Prediction, Stock Price Prediction

We investigate the importance of text analysis for stock price prediction. In particular, we introduce a system that forecasts companiesÂ’ stock price changes (UP, DOWN, STAY) in response to financial events reported in 8-K documents. Our results indicate that using text boosts prediction accuracy over 10{\%} (relative) over a strong baseline that incorporates many financially-rooted features. This impact is most important in the short term (i.e., the next day after the financial event) but persists for up to five days.
On the use of a fuzzy classifier to speed up the Sp\_ToBI labeling of the Glissando Spanish corpus
Authors: David Escudero, Lourdes Aguilar-Cuevas, C{\'e}sar Gonz{\'a}lez-Ferreras, Yurena Guti{\'e}rrez-Gonz{\'a}lez, Valent{\'\i}n Carde{\~n}oso-Payo
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5
Tasks: General Classification, Speech Recognition

In this paper, we present the application of a novel automatic prosodic labeling methodology for speeding up the manual labeling of the Glissando corpus (Spanish read news items). The methodology is based on the use of soft classification techniques. The output of the automatic system consists on a set of label candidates per word. The number of predicted candidates depends on the degree of certainty assigned by the classifier to each of the predictions. The manual transcriber checks the sets of predictions to select the correct one. We describe the fundamentals of the fuzzy classification tool and its training with a corpus labeled with Sp TOBI labels. Results show a clear coherence between the most confused labels in the output of the automatic classifier and the most confused labels detected in inter-transcriber consistency tests. More importantly, in a preliminary test, the real time ratio of the labeling process was 1:66 when the template of predictions is used and 1:80 when it is not.
Definition patterns for predicative terms in specialized lexical resources
Authors: Antonio San Mart{\'\i}n, Marie-Claude L{'}Homme
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5
Tasks: Relation

The research presented in this paper is part of a larger project on the semi-automatic generation of definitions of semantically-related terms in specialized resources. The work reported here involves the formulation of instructions to generate the definitions of sets of morphologically-related predicative terms, based on the definition of one of the members of the set. In many cases, it is assumed that the definition of a predicative term can be inferred by combining the definition of a related lexical unit with the information provided by the semantic relation (i.e. lexical function) that links them. In other words, terminographers only need to know the definition of {``}pollute{''} and the semantic relation that links it to other morphologically-related terms ({``}polluter{''}, {``}polluting{''}, {``}pollutant{''}, etc.) in order to create the definitions of the set. The results show that rules can be used to generate a preliminary set of definitions (based on specific lexical functions). They also show that more complex rules would need to be devised for other morphological pairs.
Native Language Identification Using Large, Longitudinal Data
Authors: Xiao Jiang, Yufan Guo, Jeroen Geertzen, Dora Alexopoulou, Lin Sun, Anna Korhonen
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5
Tasks: BIG-bench Machine Learning, Language Identification, Native Language Identification, Text Classification

Native Language Identification (NLI) is a task aimed at determining the native language (L1) of learners of second language (L2) on the basis of their written texts. To date, research on NLI has focused on relatively small corpora. We apply NLI to the recently released EFCamDat corpus which is not only multiple times larger than previous L2 corpora but also provides longitudinal data at several proficiency levels. Our investigation using accurate machine learning with a wide range of linguistic features reveals interesting patterns in the longitudinal data which are useful for both further development of NLI and its application to research on L2 acquisition.
Production of Phrase Tables in 11 European Languages using an Improved Sub-sentential Aligner
Authors: Juan Luo, Yves Lepage
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5
Tasks: Machine Translation, Translation

This paper is a partial report of an on-going Kakenhi project which aims to improve sub-sentential alignment and release multilingual syntactic patterns for statistical and example-based machine translation. Here we focus on improving a sub-sentential aligner which is an instance of the association approach. Phrase table is not only an essential component in the machine translation systems but also an important resource for research and usage in other domains. As part of this project, all phrase tables produced in the experiments will also be made freely available.
Construction and Annotation of a French Folkstale Corpus
Authors: Garcia-Fern, Anne ez, Anne-Laure Ligozat, Anne Vilnat
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5
Tasks: Emotion Recognition, Information Retrieval, Optical Character Recognition (OCR), POS, POS Tagging

In this paper, we present the digitization and annotation of a tales corpus - which is to our knowledge the only French tales corpus available and classified according to the Aarne{\&}Thompson classification - composed of historical texts (with old French parts). We first studied whether the pre-processing tools, namely OCR and PoS-tagging, have good enough accuracies to allow automatic analysis. We also manually annotated this corpus according to several types of information which could prove useful for future work: character references, episodes, and motifs. The contributions are the creation of an corpus of French tales from classical anthropology material, which will be made available to the community; the evaluation of OCR and NLP tools on this corpus; and the annotation with anthropological information.
The Making of Ancient Greek WordNet
Authors: Yuri Bizzoni, Federico Boschetti, Harry Diakoff, Riccardo Del Gratta, Monica Monachini, Gregory Crane
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5
Tasks: Information Retrieval, Word Sense Disambiguation

This paper describes the process of creation and review of a new lexico-semantic resource for the classical studies: AncientGreekWordNet. The candidate sets of synonyms (synsets) are extracted from Greek-English dictionaries, on the assumption that Greek words translated by the same English word or phrase have a high probability of being synonyms or at least semantically closely related. The process of validation and the web interface developed to edit and query the resource are described in detail. The lexical coverage of Ancient Greek WordNet is illustrated and the accuracy is evaluated. Finally, scenarios for exploiting the resource are discussed.
Enriching ODIN
Authors: Fei Xia, William Lewis, Michael Wayne Goodman, Joshua Crowgey, Emily M. Bender
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5

In this paper, we describe the expansion of the ODIN resource, a database containing many thousands of instances of Interlinear Glossed Text (IGT) for over a thousand languages harvested from scholarly linguistic papers posted to the Web. A database containing a large number of instances of IGT, which are effectively richly annotated and heuristically aligned bitexts, provides a unique resource for bootstrapping NLP tools for resource-poor languages. To make the data in ODIN more readily consumable by tool developers and NLP researchers, we propose a new XML format for IGT, called Xigt. We call the updated release ODIN-II.
Turkish Treebank as a Gold Standard for Morphological Disambiguation and Its Influence on Parsing
Authors: {\"O}zlem {\c{C}}etino{\u{g}}lu
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5
Tasks: Dependency Parsing, Morphological Analysis, Morphological Disambiguation

So far predicted scenarios for Turkish dependency parsing have used a morphological disambiguator that is trained on the data distributed with the tool(Sak et al., 2008). Although models trained on this data have high accuracy scores on the test and development data of the same set, the accuracy drastically drops when the model is used in the preprocessing of Turkish Treebank parsing experiments. We propose to use the Turkish Treebank(Oflazer et al., 2003) as a morphological resource to overcome this problem and convert the treebank to the morphological disambiguatorÂ’s format. The experimental results show that we achieve improvements in disambiguating the Turkish Treebank and the results also carry over to parsing. With the help of better morphological analysis, we present the best labelled dependency parsing scores to date on Turkish.
CroDeriV: a new resource for processing Croatian morphology
Authors: Kre{\v{s}}imir {\v{S}}ojat, Matea Sreba{\v{c}}i{\'c}, Marko Tadi{\'c}, Tin Paveli{\'c}
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5
Tasks: Lemmatization, Morphological Analysis

The paper deals with the processing of Croatian morphology and presents CroDeriV â€• a newly developed language resource that contains data about morphological structure and derivational relatedness of verbs in Croatian. In its present shape, CroDeriV contains 14 192 Croatian verbs. Verbs in CroDeriV are analyzed for morphemes and segmented into lexical, derivational and inflectional morphemes. The structure of CroDeriV enables the detection of verbal derivational families in Croatian as well as the distribution and frequency of particular affixes and lexical morphemes. Derivational families consist of a verbal base form and all prefixed or suffixed derivatives detected in available machine readable Croatian dictionaries and corpora. Language data structured in this way was further used for the expansion of other language resources for Croatian, such as Croatian WordNet and the Croatian Morphological Lexicon. Matching the data from CroDeriV on one side and Croatian WordNet and the Croatian Morphological Lexicon on the other resulted in significant enrichment of Croatian WordNet and enlargement of the Croatian Morphological Lexicon.
Building a Database of Japanese Adjective Examples from Special Purpose Web Corpora
Authors: Masaya Yamaguchi
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5

It is often difficult to collect many examples for low-frequency words from a single general purpose corpus. In this paper, I present a method of building a database of Japanese adjective examples from special purpose Web corpora (SPW corpora) and investigates the characteristics of examples in the database by comparison with examples that are collected from a general purpose Web corpus (GPW corpus). My proposed method construct a SPW corpus for each adjective considering to collect examples that have the following features: (i) non-bias, (ii) the distribution of examples extracted from every SPW corpus bears much similarity to that of examples extracted from a GPW corpus. The results of experiments shows the following: (i) my proposed method can collect many examples rapidly. The number of examples extracted from SPW corpora is more than 8.0 times (median value) greater than that from the GPW corpus. (ii) the distributions of co-occurrence words for adjectives in the database are similar to those taken from the GPW corpus.
Extracting a bilingual semantic grammar from FrameNet-annotated corpora
Authors: Dana Dann{\'e}lls, Normunds Gruzitis
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5
Tasks: Semantic Parsing, Text Generation

We present the creation of an English-Swedish FrameNet-based grammar in Grammatical Framework. The aim of this research is to make existing framenets computationally accessible for multilingual natural language applications via a common semantic grammar API, and to facilitate the porting of such grammar to other languages. In this paper, we describe the abstract syntax of the semantic grammar while focusing on its automatic extraction possibilities. We have extracted a shared abstract syntax from {\textasciitilde}58,500 annotated sentences in Berkeley FrameNet (BFN) and {\textasciitilde}3,500 annotated sentences in Swedish FrameNet (SweFN). The abstract syntax defines 769 frame-specific valence patterns that cover 77,8{\%} examples in BFN and 74,9{\%} in SweFN belonging to the shared set of 471 frames. As a side result, we provide a unified method for comparing semantic and syntactic valence patterns across framenets.
Mapping Between English Strings and Reentrant Semantic Graphs
Authors: Fabienne Braune, Daniel Bauer, Kevin Knight
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5
Tasks: Machine Translation, Relation

We investigate formalisms for capturing the relation between semantic graphs and English strings. Semantic graph corpora have spurred recent interest in graph transduction formalisms, but it is not yet clear whether such formalisms are a good fit for natural language dataâ€•in particular, for describing how semantic reentrancies correspond to English pronouns, zero pronouns, reflexives, passives, nominalizations, etc. We introduce a data set that focuses on these problems, we build grammars to capture the graph/string relation in this data, and we evaluate those grammars for conciseness and accuracy.