You and me... in a vector space: modelling individual speakers with distributional semantics.

The linguistic experiences of a person are an important part of their individuality. In this paper, we show that people can be modelled as vectors in a semantic space, using their personal interaction with specific language data. We also demonstrate that these vectors can be taken as representative of 'the kind of person' they are. We build over 4000 speakerdependent subcorpora using logs of Wikipedia edits, which are then used to build distributional vectors that represent individual speakers. We show that such 'person vectors' are informative to others, and they influence basic patterns of communication like the choice of one's interlocutor in conversation. Tested on an information-seeking scenario, where natural language questions must be answered by addressing the most relevant individuals in a community, our system outperforms a standard information retrieval algorithm by a considerable margin

SemEval-2018 Task 7: Semantic Relation Extraction and Classification in Scientific Papers

International audienceThis paper describes the first task on semantic relation extraction and classification in scientific paper abstracts at SemEval 2018. The challenge focuses on domain-specific semantic relations and includes three different sub-tasks. The subtasks were designed so as to compare and quantify the effect of different pre-processing steps on the relation classification results. We expect the task to be relevant for a broad range of researchers working on extracting specialized knowledge from domain corpora, for example but not limited to scientific or bio-medical information extraction. The task attracted a total of 32 participants, with 158 submissions across different scenarios

The PARSEME Shared Task on Automatic Identification of Verbal Multiword Expressions

International audienceMultiword expressions (MWEs) are known as a "pain in the neck" for NLP due to their idiosyncratic behaviour. While some categories of MWEs have been addressed by many studies, verbal MWEs (VMWEs), such as to take a decision, to break one's heart or to turn off, have been rarely modelled. This is notably due to their syntactic variability, which hinders treating them as " words with spaces ". We describe an initiative meant to bring about substantial progress in understanding, modelling and processing VMWEs. It is a joint effort, carried out within a European research network, to elaborate universal terminologies and annotation guidelines for 18 languages. Its main outcome is a multilingual 5-million-word annotated corpus which underlies a shared task on automatic identification of VMWEs. This paper presents the corpus annotation methodology and outcome, the shared task organisation and the results of the participating systems

Multiword expressions at length and in depth: Extended papers from the MWE 2017 workshop

The annual workshop on multiword expressions takes place since 2001 in conjunction with major computational linguistics conferences and attracts the attention of an ever-growing community working on a variety of languages, linguistic phenomena and related computational processing issues. MWE 2017 took place in Valencia, Spain, and represented a vibrant panorama of the current research landscape on the computational treatment of multiword expressions, featuring many high-quality submissions. Furthermore, MWE 2017 included the first shared task on multilingual identification of verbal multiword expressions. The shared task, with extended communal work, has developed important multilingual resources and mobilised several research groups in computational linguistics worldwide. This book contains extended versions of selected papers from the workshop. Authors worked hard to include detailed explanations, broader and deeper analyses, and new exciting results, which were thoroughly reviewed by an internationally renowned committee. We hope that this distinctly joint effort will provide a meaningful and useful snapshot of the multilingual state of the art in multiword expressions modelling and processing, and will be a point point of reference for future work

Multiword expressions at length and in depth: Extended papers from the MWE 2017 workshop

The annual workshop on multiword expressions takes place since 2001 in conjunction with major computational linguistics conferences and attracts the attention of an ever-growing community working on a variety of languages, linguistic phenomena and related computational processing issues. MWE 2017 took place in Valencia, Spain, and represented a vibrant panorama of the current research landscape on the computational treatment of multiword expressions, featuring many high-quality submissions. Furthermore, MWE 2017 included the first shared task on multilingual identification of verbal multiword expressions. The shared task, with extended communal work, has developed important multilingual resources and mobilised several research groups in computational linguistics worldwide. This book contains extended versions of selected papers from the workshop. Authors worked hard to include detailed explanations, broader and deeper analyses, and new exciting results, which were thoroughly reviewed by an internationally renowned committee. We hope that this distinctly joint effort will provide a meaningful and useful snapshot of the multilingual state of the art in multiword expressions modelling and processing, and will be a point point of reference for future work