10/09/2018

Mark Anderson and David Vilares have been invited to give a pair of talks at Natural Language Processing Copenhagen Meetup

For further information, please clic on the talk you are interested in

15/07/2018

Carlos Gómez-Rodríguez attended the 56th Annual Meeting of the Association for Computational Linguistics (ACL 2018) that took place in Melbourne (Australia) from July 15th through july 20th, 2018. He presented the paper:

    • Global Transition-based Non-projective Dependency Parsing

This paper presents the first practical implementations of natural language parsers that can deal with crossing dependencies and support both exact inference (via dynamic programming) and greedy inference. Thanks to the flexibility and learning capacity of minimal feature models when implemented with Bi-LSTM architectures, these algorithms, previously considered of theoretical interest only due to their prohibitive computational complexity, can now be implemented in practice with realistic runtimes, providing competitive accuracy with the state of the art.

1/06/2018

Carlos Gómez-Rodríguez, Daniel Fernández-González and David Vilares Calvo will attend the 16th Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL HLT 2018) that will take place in New Orleans (USA) from June 1st through june 6th, 2018. They will present their recent developments at the research group:

    • Improving Coverage and Runtime Complexity for Exact Inference in Non-Projective Transition-Based Dependency Parsers

This paper defines a new family of parsing algorithms supporting crossing dependencies, which have the flexibility of being compatible both with dynamic programming (an exact, but slow search method) and greedy transition-based parsing (an approximate, but fast search method). While there was one existing parser with the same flexibility, the proposed algorithms improve over it both in terms of efficiency and of coverage of the syntactic phenomena involving crossing dependencies in human languages.

    • A Dynamic Oracle for Linear-Time 2-Planar Dependency Parsing

In this article, we propose an efficient dynamic oracle for training the 2-Planar dependency parser, a well-known linear-time transition-based parser with over 99% coverage on non-projective syntactic corpora. This novel approach outperforms the traditional training strategy in the vast majority of languages tested and scored better on most datasets than the widely-used arc-hybrid parser enhanced with the SWAP transition, which can handle unrestricted non-projectivity.

    • Non-Projective Dependency Parsing with Non-Local Transitions

In this article, we present a novel transition system, based on the Covington non-projective dependency parser, introducing non-local transitions that can directly create arcs involving nodes to the left of the current focus positions. This avoids the need for long sequences of NO-ARCS transitions to create long-distance arcs, thus alleviating the main weakness of this kind of parsers: error propagation. The resulting parser outperforms the original version and achieves the best accuracy on the Penn Treebank among greedy transition-based parsers.

    • A Transition-based Algorithm for Unrestricted AMR Parsing

This paper addresses the problem of mapping the meaning of English sentences into abstract structures that are able to encode named-entities, word senses or semantic relationships between pairs of words, among other relevant information. Such structures are becoming of high interest in natural language processing, as they are of high utility by computers when dealing with tasks where semantics play a role, such as Information Extraction, Question Answering or Machine Translation.

In our work, we propose an algorithm that applies a set of transitions to transform a sequence of words into a directed, cycled, labeled graph, known as an AMR graph. The novelty of the approach comes from its simplicity to manage reentrancy and cycles, in comparison to other transition-based algorithms. The experiments have shown that this simplicity also translated into better results when identifying this particular type of edges, which are expected to happen when some of the words of the sentence are playing multiple semantic roles or when there is presence of co-reference.

For further information, please visit http://naacl2018.org/program.html

16/04/2018

Carlos Gómez-Rodriguez will attend as invited speaker the workshop THE ORIGINS AND EVOLUTION OF WORD ORDER at Evolang XII in Torun (Poland). The workshop will have three invited speakers who cover diverse areas of research on word order. Carlos will cover the topic computational linguistics:

In this talk, he will outline several ways in which the approaches used in computational linguistics to build efficient parsers for human languages are related with cognitive models of human language processing and its influence on the evolution of syntax. .

For further information, please visit https://sites.google.com/view/origins-evolution-word-order/inici

3/07/2017

Carlos Gómez-Rodríguez and Daniel Fernández-González will attend the 55th annual meeting of the Association for Computational Linguistics (ACL) that will take place in Vancouver (Canada) from July 30th through August 4th, 2017. They will present their recent developments at the research group:

    • A Full Non-Monotonic Transition System for Unrestricted Non-Projective Parsing

Efficient algorithms to parse the syntax of text in human languages typically proceed by reading sentences from left to right and building a syntactic tree at the same time, as humans are believed to do. However, this approach can run into errors when decisions are made with insufficient information, as when we have read "John bought an apple" and the next word is "tree" - only upon reading this last word, we realize that John did not buy a fruit. In this paper, we have developed an algorithm that can fix these errors by modifying previous decisions, the first of its kind that can deal with the crossing dependencies that arise in many human languages.

    • Generic Axiomatization of Families of Noncrossing Graphs in Dependency Parsing

This paper presents a novel encoding that can be used to represent various kinds of graphs used to describe the syntax and semantics of sentences in human languages, in such a way that a wide range of families of such graphs are described under the well-known framework of context-free languages. The new encoding is a theoretical development that can be exploited to define generic, efficient parsing algorithms that can be easily restricted to different families of syntactic or semantic graphs, allowing both for wide-coverage parsers and for more restricted parsers that sacrifice coverage to obtain greater efficiency.

For further information, please visit http://acl2017.org/

11/05/2017

Computer Science Department at the IT University of Copenhagen has invited Dr. Carlos Gómez-Rodríguez to give a pair of talks about Natural Language Processing. He will present an overview of the recent developments at the research group in the field of opinion mining, using natural language processing and machine learning techniques. These talks will take place:

For further information, please clic on the talk you are interested in