We describe the annotation of a new dataset for German Named Entity Recognition (NER). The need for this dataset is motivated by licensing issues and consistency issues of existing datasets. We describe our approach to creating annotation guidelines based on linguistic and semantic considerations, and how we iteratively refined and tested them in the early stages of annotation in order to arriv...

Restaurant recommendation systems are capable of recommending restaurants based on various aspects such as location, facilities and price range. There exists some research that implements restaurant recommendation systems, as well as some famous online recommendation systems such as Yelp. However, automatically rating individual food items of a restaurant based on online customer reviews is an ...

In this paper, we analyze the situation of long sequences of mostly capitalized words which look like a named entity but in fact they consist of several named entities. An example of such phenomena is hokejista (hockey player) New York Rangers Jaromír Jágr. Without splitting the sequence correctly, we will wrongly assume that the whole capitalized sequence is a name of the hockey player. To fin...

For disaster preparedness, a key aspect of the work is the identification, ahead of time, of potentially implicated locations (LOC), organizations (ORG), and persons (PER). Here we describe how static repositories of traditional news reports can be rapidly exploited to yield disasteror accident-implicated named entities.

The paper presents a collection of resources developed for Information Extraction (IE) from Polish texts. In particular, we mention two IE platforms adapted to Polish and several IE applications built on top of one of them: named entity recognition, creation of terminology lexicons, and data extraction from medical texts.

The evaluation of named entity recognition (NER) methods is an active field of research. This includes the recognition of named entities in speech transcripts. Evaluating NER systems on automatic speech recognition (ASR) output whereas human reference annotation was prepared on clean manual transcripts raises difficult alignment issues. These issues are emphasized when named entities are struct...

This paper addresses the question of hierarchical named entity evaluation. In particular, we focus on metrics to deal with complex named entity structures as those introduced within the QUAERO project. The intended goal is to propose a smart way of evaluating partially correctly detected complex entities, beyond the scope of traditional metrics. None of the existing metrics are fully adequate t...

The Third International Chinese Language Processing Bakeoff was held in Spring 2006 to assess the state of the art in two important tasks: word segmentation and named entity recognition. Twenty-nine groups submitted result sets in the two tasks across two tracks and a total of five corpora. We found strong results in both tasks as well as continuing challenges.

Matching coreferent named entities without prior knowledge requires good similarity measures. Soft-TFIDF is a fine-grained measure which performs well in this task. We propose to enhance this kind of metrics, through a generic model in which measures may be mixed, and show experimentally the relevance of this approach.

KnowNER is a multilingual Named Entity Recognition (NER) system that leverages different degrees of external knowledge. A novel modular framework divides the knowledge into four categories according to the depth of knowledge they convey. Each category consists of a set of features automatically generated from different information sources (such as a knowledge-base, a list of names or document-s...