Does referent predictability affect the choice of referential form? A computational approach using masked coreference resolution

1 code implementation • CoNLL (EMNLP) 2021 • Laura Aina, Xixian Liao, Gemma Boleda, Matthijs Westera

It is often posited that more predictable parts of a speaker's meaning tend to be made less explicit, for instance using shorter, less informative words.

coreference-resolution Referring Expression

Humans Meet Models on Object Naming: A New Dataset and Analysis

1 code implementation • COLING 2020 • Carina Silberer, Sina Zarrie{\ss}, Matthijs Westera, Gemma Boleda

We also find that standard evaluations underestimate the actual effectiveness of the naming model: on the single-label names of the original dataset (Visual Genome), it obtains −27{\%} accuracy points than on MN v2, that includes all valid object names.

Object valid

Similarity or deeper understanding? Analyzing the TED-Q dataset of evoked questions

1 code implementation • COLING 2020 • Matthijs Westera, Jacopo Amidei, Laia Mayol

We take a close look at a recent dataset of TED-talks annotated with the questions they implicitly evoke, TED-Q (Westera et al., 2020).

Binary Classification

TED-Q: TED Talks and the Questions they Evoke

no code implementations • LREC 2020 • Matthijs Westera, Laia Mayol, Hannah Rohde

We present a new dataset of TED-talks annotated with the questions they evoke and, where available, the answers to these questions.

Conversational Question Answering

Don't Blame Distributional Semantics if it can't do Entailment

no code implementations • WS 2019 • Matthijs Westera, Gemma Boleda

Our proposal sheds light on the role of distributional semantics in a broader theory of language and cognition, its relationship to formal semantics, and its place in computational models.

Semantic Similarity Semantic Textual Similarity

What do Entity-Centric Models Learn? Insights from Entity Linking in Multi-Party Dialogue

1 code implementation • NAACL 2019 • Laura Aina, Carina Silberer, Matthijs Westera, Ionut-Teodor Sorodoc, Gemma Boleda

In this paper we analyze the behavior of two recently proposed entity-centric models in a referential task, Entity Linking in Multi-party Dialogue (SemEval 2018 Task 4).

Entity Linking

AMORE-UPF at SemEval-2018 Task 4: BiLSTM with Entity Library

1 code implementation • SEMEVAL 2018 • Laura Aina, Carina Silberer, Ionut-Teodor Sorodoc, Matthijs Westera, Gemma Boleda

This paper describes our winning contribution to SemEval 2018 Task 4: Character Identification on Multiparty Dialogues.