Enrichment of Renaissance texts with proper names

International audienceThe Renom project proposes to enrich Renaissance texts by proper names. These texts present two new challenges: great diversity due to various spellings of words; numerous XML-TEI tags to save the exact format of original edition. The task consisted to add Named Entity tags to this format tagging with generally the left context and sometimes the right context of a name. To do that, we improved the free and open source program CasSys to parse texts with Unitex graph cascades and we built dictionaries and specific cascades. The slot error rate was 6.1%. Proper Names and maps. were to allow navigating into. So, this paper deals with Named Entity Recognition in Renaissance texts

Who are you, you who speak? Transducer cascades for information retrieval

International audienceThis paper deals with a survey corpus. We present information retrieval about the speaker. We used finite state transducer cascades and we present here detailed results with an evaluation. This work is part of a French project to enhance the corpus ESLO (sociolinguistic survey taken in the city of Orléans). This survey has been realized in 1968 and the project is to save records in computer format, to transcribe them and to increase the transcription with annotations in XML format. This work was supported by a French ANR contract (ANR-06-CORP-023) and by European fund from Région Centre (FEDER). The corpus represent a collection of 200 interviews with the questions about the life in the city of Orléans: How long have you lived in Orléans for?, What led you to live in Orléans?, Do you like living in Orléans?, etc. and questions about the occupation or the family of the speaker, completed by recordings within a professional or private context. The recording situations are different: interviews, discussions between friends, recordings in microphone hidden, interviews with the political, academic and religious personalities, conversations between a social worker and parents in Psycho Medical Center of Orleans. In total, we have 300 hours of speech estimated to 4,500,000 words. More precisely, we worked on almost 120 transcribed hours representing 112 Transcriber XML files and 32 577 Kb. We worked on 105 files (31 004 Kb) and we evaluated the results on 7 files (1 573 Kb-5.1%). The transcription files have no punctuation marks, but the first letter of proper names is capitalized and acronyms are fully capitalized. We used the CasSys system (Friburger, Maurel, 2004) that computes texts with transducer cascades (Abney, 1996). The cascades we used are hand built: each transducer describes a local grammar for the recognition of some entities. Some times this recognition needs the succession of two or more transducers, in a specific order. More precisely, we used two cascades; the first one, for named entity recognition, was built some years ago for a newspaper corpus and we adapted it to oral corpus in the project; the second one aimed at discovering information about the speaker in three domains: origin (is he/she Orléans city native or where he/she comes from?), family (is he/she married, with children or not?) and occupation (what is his/her occupation? where does he/she work?). We called this information designating entities. This second cascade was specifically built for the project. CasSys computes transducers with Unitex software (Paumier, 2003) that needs to segment the text by preprocessing. For written text, this segmentation usually uses sentence boundary detection (Friburger and al., 2000). In our corpus there is no punctuation. So we have chosen to use XML Transcriber tags to do the segmentation and also to hide the inside of the tag for the named entity task, sometimes ambiguous with context entities (Dister, 2007)

Automatic reconstruction of itineraries from descriptive texts

Esta tesis se inscribe dentro del marco del proyecto PERDIDO donde los objetivos son la extracción y reconstrucción de itinerarios a partir de documentos textuales. Este trabajo se ha realizado en colaboración entre el laboratorio LIUPPA de l' Université de Pau et des Pays de l' Adour (France), el grupo de Sistemas de Información Avanzados (IAAA) de la Universidad de Zaragoza y el laboratorio COGIT de l' IGN (France). El objetivo de esta tesis es concebir un sistema automático que permita extraer, a partir de guías de viaje o descripciones de itinerarios, los desplazamientos, además de representarlos sobre un mapa. Se propone una aproximación para la representación automática de itinerarios descritos en lenguaje natural. Nuestra propuesta se divide en dos tareas principales. La primera pretende identificar y extraer de los textos describiendo itinerarios información como entidades espaciales y expresiones de desplazamiento o percepción. El objetivo de la segunda tarea es la reconstrucción del itinerario. Nuestra propuesta combina información local extraída gracias al procesamiento del lenguaje natural con datos extraídos de fuentes geográficas externas (por ejemplo, gazetteers). La etapa de anotación de informaciones espaciales se realiza mediante una aproximación que combina el etiquetado morfo-sintáctico y los patrones léxico-sintácticos (cascada de transductores) con el fin de anotar entidades nombradas espaciales y expresiones de desplazamiento y percepción. Una primera contribución a la primera tarea es la desambiguación de topónimos, que es un problema todavía mal resuelto dentro del reconocimiento de entidades nombradas (Named Entity Recognition - NER) y esencial en la recuperación de información geográfica. Se plantea un algoritmo no supervisado de georreferenciación basado en una técnica de clustering capaz de proponer una solución para desambiguar los topónimos los topónimos encontrados en recursos geográficos externos, y al mismo tiempo, la localización de topónimos no referenciados. Se propone un modelo de grafo genérico para la reconstrucción automática de itinerarios, donde cada nodo representa un lugar y cada arista representa un camino enlazando dos lugares. La originalidad de nuestro modelo es que además de tener en cuenta los elementos habituales (caminos y puntos del recorrido), permite representar otros elementos involucrados en la descripción de un itinerario, como por ejemplo los puntos de referencia visual. Se calcula de un árbol de recubrimiento mínimo a partir de un grafo ponderado para obtener automáticamente un itinerario bajo la forma de un grafo. Cada arista del grafo inicial se pondera mediante un método de análisis multicriterio que combina criterios cualitativos y cuantitativos. El valor de estos criterios se determina a partir de informaciones extraídas del texto e informaciones provenientes de recursos geográficos externos. Por ejemplo, se combinan las informaciones generadas por el procesamiento del lenguaje natural como las relaciones espaciales describiendo una orientación (ej: dirigirse hacia el sur) con las coordenadas geográficas de lugares encontrados dentro de los recursos para determinar el valor del criterio ``relación espacial''. Además, a partir de la definición del concepto de itinerario y de las informaciones utilizadas en la lengua para describir un itinerario, se ha modelado un lenguaje de anotación de información espacial adaptado a la descripción de desplazamientos, apoyándonos en las recomendaciones del consorcio TEI (Text Encoding and Interchange). Finalmente, se ha implementado y evaluado las diferentes etapas de nuestra aproximación sobre un corpus multilingüe de descripciones de senderos y excursiones (francés, español, italiano)

An Analysis of the Performances of the CasEN Named Entities Recognition System in the Ester2 Evaluation Campaign

8 pagesIn this paper, we present a detailed and critical analysis of the behaviour of the CasEN named entity recognition system during the French Ester2 evaluation campaign. In this project, CasEN has been confronted with the task of detecting and categorizing named entities in manual and automatic transcriptions of radio broadcastings. At first, we give a general presentation of the Ester2 campaign. Then, we describe our system, based on transducers. Next, we depict how systems were evaluated during this campaign and we report the main official results. Afterwards, we investigate in details the influence of some annotation biases which have significantly affected the estimation of the performances of systems. At last, we conduct an in-depth analysis of the effective errors of the CasEN system, providing us with some useful indications about phenomena that gave rise to errors (e.g. metonymy, encapsulation, detection of right boundaries) and are as many challenges for named entity recognition systems

Recognition and normalization of temporal expressions in Serbian medical narratives

The temporal dimension emerges as one of the essential concepts in the field of medicine, providing a basis for the proper interpretation and understanding of medically relevant information, often recorded only in unstructured texts. Automatic processing of temporal expressions involves their identification and formalization in a language understandable to computers. This paper aims to apply the existing system for automatic processing of temporal expressions in Serbian natural language texts to medical narrative texts, to evaluate the system’s efficiency in recognition and normalization of temporal expressions and to determine the degree of necessary adaptation according to the characteristics and requirements of the medical domain

Ontology population for open-source intelligence: A GATE-based solution

Open-Source INTelligence is intelligence based on publicly available sources such as news sites, blogs, forums, etc. The Web is the primary source of information, but once data are crawled, they need to be interpreted and structured. Ontologies may play a crucial role in this process, but because of the vast amount of documents available, automatic mechanisms for their population are needed, starting from the crawled text. This paper presents an approach for the automatic population of predefined ontologies with data extracted from text and discusses the design and realization of a pipeline based on the General Architecture for Text Engineering system, which is interesting for both researchers and practitioners in the field. Some experimental results that are encouraging in terms of extracted correct instances of the ontology are also reported. Furthermore, the paper also describes an alternative approach and provides additional experiments for one of the phases of our pipeline, which requires the use of predefined dictionaries for relevant entities. Through such a variant, the manual workload required in this phase was reduced, still obtaining promising results

Toponym recognition in custom-made map titles

International audienceThe titles of customized topographic maps constitute a specific corpus which is characterized by a very significant number of place names and spelling variations. This paper is about identifying toponyms in these titles. The toponym tracking is based on gazetteers as well as light parsing according to patterns. The method used broadens the definition of the top-onym to include the nature of the corpus and the data in it. It consists of seven successive stages where both the extralinguistic context-in this case toponym georeferencing-and the linguistic context are taken into account. Mistakes in tagging are analyzed from the corpus characteristics and the results of each step tagging are evaluated (recall, precision, F-measure). Different conclusions can be suggested: i) toponym recognition in web corpora should take into account spelling changes, ii) toponym recognition cannot be limited to gazetteer proper nouns, iii) the notion of subjective toponym is relevant in this specific corpus, and could be considered with reference to the customization of maps