Search Results for author: Kiril Gashteovski

Found 18 papers, 10 papers with code

On Aligning OpenIE Extractions with Knowledge Bases: A Case Study

no code implementations EMNLP (Eval4NLP) 2020 Kiril Gashteovski, Rainer Gemulla, Bhushan Kotnis, Sven Hertling, Christian Meilicke

First, we investigate OPIEC triples and DBpedia facts having the same arguments by comparing the information on the OIE surface relation with the KB rela- tion.

Open Information Extraction

LightPAL: Lightweight Passage Retrieval for Open Domain Multi-Document Summarization

no code implementations18 Jun 2024 Masafumi Enomoto, Kunihiro Takeoka, Kosuke Akimoto, Kiril Gashteovski, Masafumi Oyamada

Open-Domain Multi-Document Summarization (ODMDS) is crucial for addressing diverse information needs, which aims to generate a summary as answer to user's query, synthesizing relevant content from multiple documents in a large collection.

AgentQuest: A Modular Benchmark Framework to Measure Progress and Improve LLM Agents

1 code implementation9 Apr 2024 Luca Gioacchini, Giuseppe Siracusano, Davide Sanvito, Kiril Gashteovski, David Friede, Roberto Bifulco, Carolin Lawrence

The advances made by Large Language Models (LLMs) have led to the pursuit of LLM agents that can solve intricate, multi-step reasoning tasks.

Benchmarking

Robust Text Classification: Analyzing Prototype-Based Networks

no code implementations11 Nov 2023 Zhivar Sourati, Darshan Deshpande, Filip Ilievski, Kiril Gashteovski, Sascha Saralajew

In this paper, we study whether the robustness properties of PBNs transfer to text classification tasks under both targeted and static adversarial attack settings.

Sentence text-classification +1

Linking Surface Facts to Large-Scale Knowledge Graphs

1 code implementation23 Oct 2023 Gorjan Radevski, Kiril Gashteovski, Chia-Chien Hung, Carolin Lawrence, Goran Glavaš

Open Information Extraction (OIE) methods extract facts from natural language text in the form of ("subject"; "relation"; "object") triples.

Knowledge Graphs Open Information Extraction

Large Language Models Enable Few-Shot Clustering

1 code implementation2 Jul 2023 Vijay Viswanathan, Kiril Gashteovski, Carolin Lawrence, Tongshuang Wu, Graham Neubig

In this paper, we ask whether a large language model can amplify an expert's guidance to enable query-efficient, few-shot semi-supervised text clustering.

Clustering Language Modelling +2

Leveraging Open Information Extraction for More Robust Domain Transfer of Event Trigger Detection

1 code implementation23 May 2023 David Dukić, Kiril Gashteovski, Goran Glavaš, Jan Šnajder

We address the problem of negative transfer in TD by coupling triggers between domains using subject-object relations obtained from a rule-based open information extraction (OIE) system.

Event Detection Language Modelling +2

Human-Centric Research for NLP: Towards a Definition and Guiding Questions

no code implementations10 Jul 2022 Bhushan Kotnis, Kiril Gashteovski, Julia Gastinger, Giuseppe Serra, Francesco Alesiani, Timo Sztyler, Ammar Shaker, Na Gong, Carolin Lawrence, Zhao Xu

With Human-Centric Research (HCR) we can steer research activities so that the research outcome is beneficial for human stakeholders, such as end users.

A Human-Centric Assessment Framework for AI

no code implementations25 May 2022 Sascha Saralajew, Ammar Shaker, Zhao Xu, Kiril Gashteovski, Bhushan Kotnis, Wiem Ben Rim, Jürgen Quittek, Carolin Lawrence

Inspired by the Turing test, we introduce a human-centric assessment framework where a leading domain expert accepts or rejects the solutions of an AI system and another domain expert.

milIE: Modular & Iterative Multilingual Open Information Extraction

no code implementations ACL 2022 Bhushan Kotnis, Kiril Gashteovski, Daniel Oñoro Rubio, Vanesa Rodriguez-Tembras, Ammar Shaker, Makoto Takamoto, Mathias Niepert, Carolin Lawrence

In contrast, we explore the hypothesis that it may be beneficial to extract triple slots iteratively: first extract easy slots, followed by the difficult ones by conditioning on the easy slots, and therefore achieve a better overall extraction.

Open Information Extraction

Can We Predict New Facts with Open Knowledge Graph Embeddings? A Benchmark for Open Link Prediction

1 code implementation ACL 2020 Samuel Broscheit, Kiril Gashteovski, Yanjie Wang, Rainer Gemulla

An evaluation in such a setup raises the question if a correct prediction is actually a new fact that was induced by reasoning over the open knowledge graph or if it can be trivially explained.

Knowledge Graph Embeddings Link Prediction +3

MinScIE: Citation-centered Open Information Extraction

1 code implementation Joint Conference on Digital Libraries (JCDL) 2019 Anne Lauscher, Yide Song, Kiril Gashteovski

Acknowledging the importance of citations in scientific literature, in this work we present MinScIE, an Open Information Extraction system which provides structured knowledge enriched with semantic information about citations.

Open Information Extraction

MinIE: Minimizing Facts in Open Information Extraction

1 code implementation EMNLP 2017 Kiril Gashteovski, Rainer Gemulla, Luciano del Corro

The goal of Open Information Extraction (OIE) is to extract surface relations and their arguments from natural-language text in an unsupervised, domain-independent manner.

Open Information Extraction Question Answering +1

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