Articles

In order to make the temporal interpretation of text, there have been many studies linking event and temporal information, such as temporal ordering of events and timeline generation. To train and evaluate models in these studies, many corpora that associate event information with time information have been developed. In this …...

Temporal sense detection of any word is an important aspect for detecting temporality at the sentence level. In this paper, at first, we build a temporal resource based on a semi-supervised learning approach where each Hindi-WordNet synset is classified into one of the five classes, namely past, present, future, neutral …...

Specific-domain bilingual lexicons play an important role for domain adaptation in machine translation. The entries of these types of lexicons are mostly composed of MultiWord Expressions (MWEs). The manual construction of MWEs bilingual lexicons is costly and time-consuming. We often use word alignment approaches to automatically construct bilingual lexicons of …...

One of the major challenges in the field of Natural Language Processing (NLP) is the handling of idioms; seemingly ordinary phrases which could be further conjugated or even spread across the sentence to fit the context. Since idioms are a part of natural language, the ability to tackle them brings …...

We present and make available a large automatically-acquired all-words list of English multiword expressions scored for compositionality. Intrinsic evaluation against manually-produced gold standards demonstrates that our compositionality estimates are sound, and extrinsic evaluation via incorporation of our list into a machine translation system to better handle idiomatic expressions results in …...

The acquisition of synonyms and quasi-synonyms of multi-word terms (MWTs) is a relatively new and under represented topic of research. However, dealing with MWT synonyms and semantically related terms is a challenging task, especially when MWT synonyms are single word terms (SWTs) or MWTs of different lengths. While several researches …...

In this paper, we present our process to establish a PICO and a sentiment annotated corpus of clinical trial publications. PICO stands for Population, Intervention, Comparison and Outcome — these four classes can be used for more advanced and specific search queries. For example, a physician can determine how well …...

A vast amount of biomedical information is available in the form of scientific literature and government-authored patient information documents. While English is the most widely used language in many of these sources, there is a need to provide access to health information in languages other than English. Parallel corpora can …...

We present a new corpus of 200 abstracts and 100 full text papers which have been annotated with named entities and relations in the biomedical domain as part of the OpenMinTeD project. This corpus facilitates the goal in OpenMinTeD of making text and data mining accessible to the users who …...

The object of this article is to describe the extraction of data from a corpus of academic texts in Spanish and the use of those data for developing a lexical tool oriented to the production of academic texts. The corpus provides the lexical combinations that will be included in the …...

This paper presents a pilot project named Cancer FrameNet. The project’s goal is a general-purpose natural language processing (NLP) resource for cancer-related information in clinical notes (i.e., patient records in an electronic health record system). While previous cancer NLP annotation projects have largely been ad hoc resources to address a …...

Named Entity Linking (NEL) and relation extraction forms the backbone of Knowledge Base Population tasks. The recent rise of large open source Knowledge Bases and the continuous focus on improving NEL performance has led to the creation of automated benchmark solutions during the last decade. The benchmarking of NEL systems …...

In this paper, we present a corpus of over 11,000 holiday picture postcards written in German and Swiss German. The postcards have been collected for the purpose of text-linguistic investigations on the genre and its standardisation and variation over time. We discuss the processes and challenges of digitalisation, manual transcription, …...

This paper describes an English audio and textual dataset of debating speeches, a unique resource for the growing research field of computational argumentation and debating technologies. We detail the process of speech recording by professional debaters, the transcription of the speeches with an Automatic Speech Recognition (ASR) system, their consequent …...

Automatic language identification of an input sentence or a text written in similar languages, varieties or dialects is an important task in natural language processing. In this paper, we propose a scheme to represent Gan (Jiangxi province of China) Chinese dialects. In particular, it is a two-level and fine-grained representation …...

Paraphrases play an important role in natural language understanding, especially because there are fluent jumps between hidden paraphrases in a text. For example, even to get to the meaning of a simple dialog like I bought a computer. How much did the computer cost? involves quite a few steps. A …...

Word embeddings capture a string’s semantics and go beyond its surface form. In a multilingual environment, those embeddings need to be trained for each language, either separately or as a joint model. The more languages needed, the more computationally cost- and time-intensive the task of training. As an alternative, pretrained …...

Knowledge-based question answering relies on the availability of facts, the majority of which cannot be found in structured sources (e.g. Wikipedia info-boxes, Wikidata). One of the major components of extracting facts from unstructured text is Relation Extraction (RE). In this paper we propose a novel method for creating distant (weak) …...

Methods for learning lower-dimensional representations (embeddings) of words using unlabelled data have received a renewed interested due to their myriad success in various Natural Language Processing (NLP) tasks. However, despite their success, a common deficiency associated with most word embedding learning methods is that they learn a single representation for …...

Building a Knowledge Base from text corpora is useful for many applications such as question answering and web search. Since 2012, the Cold Start Knowledge Base Population (KBP) evaluation at the Text Analysis Conference (TAC) has attracted many participants. Despite the popularity, the Cold Start KBP evaluation has several problems …...