CLTL papers, oral presentations, poster & demo sessions at LREC2016: 10th edition of the Language Resources and Evaluation Conference, 23-28 May 2016, Portorož (Slovenia)

LREC2016 Conference Programme

Monday 23 May 2016

11.00 – 11.45 (Session 2: Lightning talks part II)
“Multilingual Event Detection using the NewsReader Pipelines”, by Agerri R, I. Aldabe, E. Laparra, G. Rigau, A. Fokkens, P. Huijgen, R. Izquierdo, M. van Erp, Piek Vossen, A. Minard, B. Magnini

Abstract
We describe a novel modular system for cross-lingual event extraction for English, Spanish,, Dutch and Italian texts. The system consists of a ready-to-use modular set of advanced multilingual Natural Language Processing (NLP) tools. The pipeline integrates modules for basic NLP processing as well as more advanced tasks such as cross-lingual Named Entity Linking, Semantic Role Labeling and time normalization. Thus, our cross-lingual framework allows for the interoperable semantic interpretation of events, participants, locations and time, as well as the relations between them.

Tuesday 24 May 2016

09:15 – 10:30 Oral Session 1
“Stereotyping and Bias in the Flickr30k Dataset” by Emiel van Miltenburg

Abstract
An untested assumption behind the crowdsourced descriptions of the images in the Flickr30k dataset (Young et al., 2014) is that they “focus only on the information that can be obtained from the image alone” (Hodosh et al., 2013, p. 859). This paper presents some evidence against this assumption, and provides a list of biases and unwarranted inferences that can be found in the Flickr30k dataset. Finally, it considers methods to find examples of these, and discusses how we should deal with stereotypedriven descriptions in future applications.

Day 1, Wednesday 25 May 2016

11:35 – 13:15 Area 1 – P04 Information Extraction and Retrieval
“NLP and public engagement: The case of the Italian School Reform” by Tommaso Caselli, Giovanni Moretti, Rachele Sprugnoli, Sara Tonelli, Damien Lanfrey and Donatella Solda Kutzman

Abstract
In this paper we present PIERINO (PIattaforma per l’Estrazione e il Recupero di INformazione Online), a system that was implemented in collaboration with the Italian Ministry of Education, University and Research to analyse the citizens’ comments given in #labuonascuola survey. The platform includes various levels of automatic analysis such as key-concept extraction and word co-occurrences. Each analysis is displayed through an intuitive view using different types of visualizations, for example radar charts and sunburst. PIERINO was effectively used to support shaping the last Italian school reform, proving the potential of NLP in the context of policy making.

15:05 – 16:05 Emerald 2 – O8 Named Entity Recognition
“Context-enhanced Adaptive Entity Linking” by Giuseppe Rizzo, Filip Ilievski, Marieke van Erp, Julien Plu and Raphael Troncy

Abstract
More and more knowledge bases are publicly available as linked data. Since these knowledge bases contain structured descriptions of real-world entities, they can be exploited by entity linking systems that anchor entity mentions from text to the most relevant resources describing those entities. In this paper, we investigate adaptation of the entity linking task using contextual knowledge. The key intuition is that entity linking can be customized depending on the textual content, as well as on the application that would make use of the extracted information. We present an adaptive approach that relies on contextual knowledge from text to enhance the performance of ADEL, a hybrid linguistic and graph-based entity linking system. We evaluate our approach on a domain-specific corpus consisting of annotated WikiNews articles.

16:45 – 18:05 – Area 1 – P12
“GRaSP: A multi-layered annotation scheme for perspectives” by Chantal van Son, Tommaso Caselli, Antske Fokkens, Isa Maks, Roser Morante, Lora Aroyo and Piek Vossen

Abstract / Poster
This paper presents a framework and methodology for the annotation of perspectives in text. In the last decade, different aspects of linguistic encoding of perspectives have been targeted as separated phenomena through different annotation initiatives. We propose an annotation scheme that integrates these different phenomena. We use a multilayered annotation approach, splitting the annotation of different aspects of perspectives into small subsequent subtasks in order to reduce the complexity of the task and to better monitor interactions between layers. Currently, we have included four layers of perspective annotation: events, attribution, factuality and opinion. The annotations are integrated in a formal model called GRaSP, which provides the means to represent instances (e.g. events, entities) and propositions in the (real or assumed) world in relation to their mentions in text. Then, the relation between the source and target of a perspective is characterized by means of perspective annotations. This enables us to place alternative perspectives on the same entity, event or proposition next to each other.

18:10 – 19:10 – Area 2 – P16 Ontologies
“The Event and Implied Situation Ontology: Application and Evaluation” by Roxane Segers, Marco Rospocher, Piek Vossen, Egoitz Laparra, German Rigau, Anne-Lyse Minard

Abstract / Poster
This paper presents the Event and Implied Situation Ontology (ESO), a manually constructed resource which formalizes the pre and post situations of events and the roles of the entities affected by an event. The ontology is built on top of existing resources such as WordNet, SUMO and FrameNet. The ontology is injected to the Predicate Matrix, a resource that integrates predicate and role information from amongst others FrameNet, VerbNet, PropBank, NomBank and WordNet. We illustrate how these resources are used on large document collections to detect information that otherwise would have remained implicit. The ontology is evaluated on two aspects: recall and precision based on a manually annotated corpus and secondly, on the quality of the knowledge inferred by the situation assertions in the ontology. Evaluation results on the quality of the system show that 50% of the events typed and enriched with ESO assertions are correct.

Day 2, Thursday 26 May 2016

10.25 – 10.45 – O20
“Addressing the MFS bias in WSD systems” by Marten Postma, Ruben Izquierdo, Eneko Agirre, German Rigau and Piek Vossen

Abstract
This paper presents a framework and methodology for the annotation of perspectives in text. In the last decade, different aspects of linguistic encoding of perspectives have been targeted as separated phenomena through different annotation initiatives. We propose an annotation scheme that integrates these different phenomena. We use a multilayered annotation approach, splitting the annotation of different aspects of perspectives into small subsequent subtasks in order to reduce the complexity of the task and to better monitor interactions between layers. Currently, we have included four layers of perspective annotation: events, attribution, factuality and opinion. The annotations are integrated in a formal model called GRaSP, which provides the means to represent instances (e.g. events, entities) and propositions in the (real or assumed) world in relation to their mentions in text. Then, the relation between the source and target of a perspective is characterized by means of perspective annotations. This enables us to place alternative perspectives on the same entity, event or proposition next to each other.

11.45 – 13.05 – Area 2 – P25
“The VU Sound Corpus: Adding more fine-grained annotations to the Freesound database” by Emiel van Miltenburg, Benjamin Timmermans and Lora Aroyo

Day 3, Friday 27 May 2016

10.45 – 11.05 – O38
“Temporal Information Annotation: Crowd vs. Experts” by Tommaso Caselli, Rachele Sprugnoli and Oana Inel

Abstract
This paper describes two sets of crowdsourcing experiments on temporal information annotation conducted on two languages, i.e., English and Italian. The first experiment, launched on the CrowdFlower platform, was aimed at classifying temporal relations given target entities. The second one, relying on the CrowdTruth metric, consisted in two subtasks: one devoted to the recognition of events and temporal expressions and one to the detection and classification of temporal relations. The outcomes of the experiments suggest a valuable use of crowdsourcing annotations also for a complex task like Temporal Processing.

12.45 – 13.05 – O42
“Crowdsourcing Salient Information from News and Tweets” by Oana Inel, Tommaso Caselli and Lora Aroyo

Abstract
The increasing streams of information pose challenges to both humans and machines. On the one hand, humans need to identify relevant information and consume only the information that lies at their interests. On the other hand, machines need to understand the information that is published in online data streams and generate concise and meaningful overviews. We consider events as prime factors to query for information and generate meaningful context. The focus of this paper is to acquire empirical insights for identifying salience features in tweets and news about a target event, i.e., the event of “whaling”. We first derive a methodology to identify such features by building up a knowledge space of the event enriched with relevant phrases, sentiments and ranked by their novelty. We applied this methodology on tweets and we have performed preliminary work towards adapting it to news articles. Our results show that crowdsourcing text relevance, sentiments and novelty (1) can be a main step in identifying salient information, and (2) provides a deeper and more precise understanding of the data at hand compared to state-of-the-art approaches.

14:55 – 16:15 – Area 2- P54
“Two architectures for parallel processing for huge amounts of text” by Mathijs Kattenberg, Zuhaitz Beloki, Aitor Soroa, Xabier Artola, Antske Fokkens, Paul Huygen and Kees Verstoep

Abstract
This paper presents two alternative NLP architectures to analyze massive amounts of documents, using parallel processing. The two architectures focus on different processing scenarios, namely batch-processing and streaming processing. The batch-processing scenario aims at optimizing the overall throughput of the system, i.e., minimizing the overall time spent on processing all documents. The streaming architecture aims to minimize the time to process real-time incoming documents
and is therefore especially suitable for live feeds. The paper presents experiments with both architectures, and reports the overall gain when they are used for batch as well as for streaming processing. All the software described in the paper is publicly available under free licenses.

14:55 – 15:15 Emerald 1 – O47
“Evaluating Entity Linking: An Analysis of Current Benchmark Datasets and a Roadmap for Doing a Better Job” by Marieke van Erp, Pablo Mendes, Heiko Paulheim, Filip Ilievski, Julien Plu, Giuseppe Rizzo and Joerg Waitelonis

Abstract
Entity linking has become a popular task in both natural language processing and semantic web communities. However, we find that the benchmark datasets for entity linking tasks do not accurately evaluate entity linking systems. In this paper, we aim to chart the strengths and weaknesses of current benchmark datasets and sketch a roadmap for the community to devise better benchmark datasets.

15.35 – 15.55 – O48
“MEANTIME, the NewsReader Multilingual Event and Time Corpus” by Anne-Lyse Minard, Manuela Speranza, Ruben Urizar, Begoña Altuna, Marieke van Erp, Anneleen Schoen and Chantal van Son

Abstract
In this paper, we present the NewsReader MEANTIME corpus, a semantically annotated corpus of Wikinews articles. The corpus consists of 480 news articles, i.e. 120 English news articles and their translations in Spanish, Italian, and Dutch. MEANTIME contains annotations at different levels. The document-level annotation includes markables (e.g. entity mentions, event mentions, time expressions, and numerical expressions), relations between markables (modeling, for example, temporal information and semantic role labeling), and entity and event intra-document coreference. The corpus-level annotation includes entity and event cross-document coreference. Semantic annotation on the English section was performed manually; for the annotation in Italian, Spanish, and (partially) Dutch, a procedure was devised to automatically project the annotations on the English texts onto the translated texts, based on the manual alignment of the annotated elements; this enabled us not only to speed up the annotation process but also provided cross-lingual coreference. The English section of the corpus was extended with timeline annotations for the SemEval 2015 TimeLine shared task. The First CLIN Dutch Shared Task at CLIN26 was based on the Dutch section, while the EVALITA 2016 FactA (Event Factuality Annotation) shared task, based on the Italian section, is currently being organized.