This shared task focuses on identifying unusual, previously-unseen entities in the context of emerging discussions. Named entities form the basis of many modern approaches to other tasks (like event clustering and summarization), but recall on them is a real problem in noisy text even among annotators. This drop tends to be due to novel entities and surface forms. Take for example the tweet “so...

We describe a simple IR approach for linking news about events, detected by an event extraction system, to messages from Twitter (tweets). In particular, we explore several methods for creating event-specific queries for Twitter and provide a quantitative and qualitative evaluation of the relevance and usefulness of the information obtained from the tweets. We showed that methods based on utili...

Named entity recognition (NER) is a subtask of information extraction (IE) which can be used further on for different purposes. In this paper, we discuss named entity recognition for Ukrainian language, which is a Slavonic language with a rich morphology. The approach we follow uses a restricted number of features. We show that it is feasible to boost performance by considering several heuristi...

It has recently been suggested that the nervous system employs forward models for the purpose of motor control. The evidence for this hypothetical computational structure comes from various sources, theoretical and experimental. The purpose of this commentary is to distinguish between three different structures that are used to support the forward model hypothesis: (1) output predictor, (2) sta...

One of issues in the bootstrapping for named entity recognition is how to control annotation errors introduced at every iteration. In this paper, we present several heuristics for reducing such errors using external resources such as WordNet, encyclopedia and Web documents. The bootstrapping is applied for identifying and classifying fine-grained geographic named entities, which are useful for ...

This paper presents a statistics-based and language independent unsupervised approach for clustering possible named entities. We describe and motivate the features and statistical filters used by our clustering process. Using the Model-Based Clustering Analysis software we obtained different clusters of named entities. The method was applied to Bulgarian and English. For some clusters, precisio...

Finding automatic ways of attaching geographical scopes to on-line resources, also called “geo-referencing” documents, is a challenging problem, getting increasing attention [1, 5, 3]. Here we present a system architecture and a process for identifying the geographical scope of Web pages, defining a scope as the region where more people than average would find that page relevant. We rely on typ...