Search Results for author: Sean Papay

Found 8 papers, 1 papers with code

Actor Identification in Discourse: A Challenge for LLMs?

no code implementations1 Feb 2024 Ana Barić, Sean Papay, Sebastian Padó

The identification of political actors who put forward claims in public debate is a crucial step in the construction of discourse networks, which are helpful to analyze societal debates.

Constraining Linear-chain CRFs to Regular Languages

1 code implementation ICLR 2022 Sean Papay, Roman Klinger, Sebastian Padó

However, the CRF's Markov assumption makes it impossible for CRFs to represent distributions with \textit{nonlocal} dependencies, and standard CRFs are unable to respect nonlocal constraints of the data (such as global arity constraints on output labels).

Semantic Role Labeling Structured Prediction

Dissecting Span Identification Tasks with Performance Prediction

no code implementations EMNLP 2020 Sean Papay, Roman Klinger, Sebastian Padó

Span identification (in short, span ID) tasks such as chunking, NER, or code-switching detection, ask models to identify and classify relevant spans in a text.

Chunking NER

IMS at SemEval-2020 Task 1: How low can you go? Dimensionality in Lexical Semantic Change Detection

no code implementations SEMEVAL 2020 Jens Kaiser, Dominik Schlechtweg, Sean Papay, Sabine Schulte im Walde

We present the results of our system for SemEval-2020 Task 1 that exploits a commonly used lexical semantic change detection model based on Skip-Gram with Negative Sampling.

Change Detection

RiQuA: A Corpus of Rich Quotation Annotation for English Literary Text

no code implementations LREC 2020 Sean Papay, Sebastian Pad{\'o}

We introduce RiQuA (RIch QUotation Annotations), a corpus that provides quotations, including their interpersonal structure (speakers and addressees) for English literary text.

Quotation Detection and Classification with a Corpus-Agnostic Model

no code implementations RANLP 2019 Sean Papay, Sebastian Pad{\'o}

The detection of quotations (i. e., reported speech, thought, and writing) has established itself as an NLP analysis task.

Classification General Classification

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