Ludovic Jean-Louis

• PhD
• Engineer at Netmail Inc

Slot Filling, a subtask of Relation Extraction, represents a key aspect for building structured knowledge bases usable for semantic-based information retrieval. In this work, we present a machine learning filter whose aim is to enhance the precision of relation extractors while minimizing the impact on the recall. Our approach consists in the filte...

Open relation extraction has been a growing field of research in the last few years. This paper compares some of the most prominent open relation extractors and explores their strength and weaknesses on standard datasets. In particular, we highlight the lack of formal guidelines that define a valid relation and state that open relation extractors m...

This work presents the bioMine system, a full-text natural language search engine for biomedical literature. bioMine provides search capabilities based on the full-text content of documents belonging to a database composed of scientific articles and allows users to submit their search queries using natural language. Beyond the text content of artic...

This paper presents the ongoing development of a full-text natural language search engine for biomedical literature. The system aims to provide search on the full-text content of documents belonging to a database composed of scientific articles, while allowing users to submit their search queries using natural language. Beyond the text content of a...

The TAC KBP English slot filling track is an evaluation campaign that targets the extraction of 41 pre-identified relations related to specific named entities. In this work, we present a machine learning filter whose aim is to enhance the precision of relation extractors while minimizing the impact on recall. Our approach aims at filtering relation...

The task of keyword extraction aims at capturing expressions (or entities) that best represent the main topics of a document. Given the rapid adoption of these online semantic annotators and their contribution to the growth of the Semantic Web, one important task is to assess their quality. This article presents an evaluation of the quality and sta...

The disambiguation algorithm presented in this paper is implemented in SemLinker, an entity linking system. First, named entities are linked to candidate Wikipedia pages by a generic annotation engine. Then, the algorithm re-ranks candidate links according to mutual relations between all the named entities found in the document. The evaluation is b...

In this paper, we present an algorithm for improving named entity resolution and entity linking by using surface form generation and rewriting. Surface forms consist of a word or a group of words that matches lexical units like Paris or New York City. Used as matching sequences to select candidate entries in a knowledge base, they contribute to the...

Numerous initiatives have allowed users to share knowledge or opinions using collaborative platforms. In most cases, the users provide a textual description of their knowledge, following very limited or no constraints. Here, we tackle the classification of documents written in such an environment. As a use case, our study is made in the context of...

Wikimeta Lab participation in DeFT 2013 - Machine Learning for Information Extraction and Classification of Cooking Recipes. This paper presents Wikimeta Lab participation in the Défi Fouille de Texte (DeFT) 2013. In 2013, this evaluation campaign is focused on mining cooking recipes in French. The campaign consists of three classification tasks an...

Automatic keyword extraction is an important subfield of information extraction process. It is a difficult task, where numerous different techniques and resources have been proposed. In this paper, we propose a generic approach to extract keyword from documents using encyclopedic knowledge. Our two-step approach first relies on a classification ste...

Semantic annotation is the process of identifying expressions in texts and linking them to some semantic structure. In particular, Linked data-based Semantic Annotators are now becoming the new Holy Grail for meaning extraction from unstructured documents. This paper presents an evaluation of the main linked data-based annotators available with a f...

Automatic keyword extraction is an important subfield of information extraction process. It is a difficult task, where numerous different techniques and resources have been proposed. In this paper, we propose a generic approach to extract keyword from documents using encyclopedic knowledge. Our two-step approach first relies on a classification ste...

Most of Information Extraction (IE) systems are designed for extracting a restricted number of relations in a specific domain. Recent work about Web-scale knowledge extraction has changed this perspective by introducing large-scale IE systems. Such systems are open-domain and characterized by a large number of relations, which makes traditional app...

The major part of the information available on the web is provided in textual form, i.e. in unstructured form. In a context such as technology watch, it is useful to present the information extracted from a text in a structured form, reporting only the pieces of information that are relevant to the considered field of interest. Such processing cann...

In event-based Information Extraction systems, a major task is the filling from a text of a template gathering information related to a particular event. Such template filling may be a hard task when the information is scattered throughout the text and mixed with similar pieces of information relative to different events. We propose in this paper a...

Operational intelligence applications in specific domains are developed using numerous natural language processing technologies and tools. A challenge for this integration is to take into account the limitations of each of these technologies in the global evaluation of the application. We present in this article an intelligence application for the...

One of the early application of Information Extraction, motivated by the needs for intelligence tools, is the detection of events in news articles. But this detection may be difficult when news articles mention several occurrences of events of the same kind, which is often done for comparison purposes. We propose in this article new approaches to s...

Résumé. Les systèmes d'extraction d'information traditionnels se focalisent sur un domaine spécifique et un nombre limité de relations. Les travaux récents dans ce domaine ont cependant vu émerger la problématique des systèmes d'extraction d'information à large échelle. À l'instar des systèmes de question-réponse en domaine ouvert, ces systèmes se...

We present in this article the system we devel-oped for participating to the slot filling task in the Knowledge Base Population (KBP) track of the 2011 Text Analysis Conference (TAC). This system is based on a weakly supervised approach and lexical patterns. In this partic-ipation, we tested more specifically the inte-gration of an additional unsup...

In event-based Information Extraction sys-tems, a major task is the automated fill-ing from unstructured texts of a template gathering information related to a partic-ular event. Such template filling may be a hard task when the information is scattered throughout the text and mixed with similar pieces of information relative to a differ-ent event....