Stefan Bott


Factoring Ambiguity out of the Prediction of Compositionality for German Multi-Word Expressions
Stefan Bott | Sabine Schulte im Walde
Proceedings of the 13th Workshop on Multiword Expressions (MWE 2017)

Ambiguity represents an obstacle for distributional semantic models(DSMs), which typically subsume the contexts of all word senses within one vector. While individual vector space approaches have been concerned with sense discrimination (e.g., Schütze 1998, Erk 2009, Erk and Pado 2010), such discrimination has rarely been integrated into DSMs across semantic tasks. This paper presents a soft-clustering approach to sense discrimination that filters sense-irrelevant features when predicting the degrees of compositionality for German noun-noun compounds and German particle verbs.


GhoSt-NN: A Representative Gold Standard of German Noun-Noun Compounds
Sabine Schulte im Walde | Anna Hätty | Stefan Bott | Nana Khvtisavrishvili
Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)

This paper presents a novel gold standard of German noun-noun compounds (Ghost-NN) including 868 compounds annotated with corpus frequencies of the compounds and their constituents, productivity and ambiguity of the constituents, semantic relations between the constituents, and compositionality ratings of compound-constituent pairs. Moreover, a subset of the compounds containing 180 compounds is balanced for the productivity of the modifiers (distinguishing low/mid/high productivity) and the ambiguity of the heads (distinguishing between heads with 1, 2 and >2 senses

GhoSt-PV: A Representative Gold Standard of German Particle Verbs
Stefan Bott | Nana Khvtisavrishvili | Max Kisselew | Sabine Schulte im Walde
Proceedings of the 5th Workshop on Cognitive Aspects of the Lexicon (CogALex - V)

German particle verbs represent a frequent type of multi-word-expression that forms a highly productive paradigm in the lexicon. Similarly to other multi-word expressions, particle verbs exhibit various levels of compositionality. One of the major obstacles for the study of compositionality is the lack of representative gold standards of human ratings. In order to address this bottleneck, this paper presents such a gold standard data set containing 400 randomly selected German particle verbs. It is balanced across several particle types and three frequency bands, and accomplished by human ratings on the degree of semantic compositionality.

The Role of Modifier and Head Properties in Predicting the Compositionality of English and German Noun-Noun Compounds: A Vector-Space Perspective
Sabine Schulte im Walde | Anna Hätty | Stefan Bott
Proceedings of the Fifth Joint Conference on Lexical and Computational Semantics


Exploiting Fine-grained Syntactic Transfer Features to Predict the Compositionality of German Particle Verbs
Stefan Bott | Sabine Schulte im Walde
Proceedings of the 11th International Conference on Computational Semantics


Syntactic Transfer Patterns of German Particle Verbs and their Impact on Lexical Semantics
Stefan Bott | Sabine Schulte im Walde
Proceedings of the Third Joint Conference on Lexical and Computational Semantics (*SEM 2014)

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Modelling Regular Subcategorization Changes in German Particle Verbs
Stefan Bott | Sabine Schulte im Walde
Proceedings of the First Workshop on Computational Approaches to Compound Analysis (ComAComA 2014)

Optimizing a Distributional Semantic Model for the Prediction of German Particle Verb Compositionality
Stefan Bott | Sabine Schulte im Walde
Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14)

In the work presented here we assess the degree of compositionality of German Particle Verbs with a Distributional Semantics Model which only relies on word window information and has no access to syntactic information as such. Our method only takes the lexical distributional distance between the Particle Verb to its Base Verb as a predictor for compositionality. We show that the ranking of distributional similarity correlates significantly with the ranking of human judgements on semantic compositionality for a series of Particle Verbs and the Base Verbs they are derived from. We also investigate the influence of further linguistic factors, such as the ambiguity and the overall frequency of the verbs and a syntactically separate occurrences of verbs and particles that causes difficulties for the correct lemmatization of Particle Verbs. We analyse in how far these factors may influence the success with which the compositionality of the Particle Verbs may be predicted.


Text Simplification Tools for Spanish
Stefan Bott | Horacio Saggion | Simon Mille
Proceedings of the Eighth International Conference on Language Resources and Evaluation (LREC'12)

In this paper we describe the development of a text simplification system for Spanish. Text simplification is the adaptation of a text to the special needs of certain groups of readers, such as language learners, people with cognitive difficulties and elderly people, among others. There is a clear need for simplified texts, but manual production and adaptation of existing texts is labour intensive and costly. Automatic simplification is a field which attracts growing attention in Natural Language Processing, but, to the best of our knowledge, there are no simplification tools for Spanish. We present a prototype for automatic simplification, which shows that the most important structural simplification operations can be successfully treated with an approach based on rules which can potentially be improved by statistical methods. For the development of this prototype we carried out a corpus study which aims at identifying the operations a text simplification system needs to carry out in order to produce an output similar to what human editors produce when they simplify texts.

A Hybrid System for Spanish Text Simplification
Stefan Bott | Horacio Saggion | David Figueroa
Proceedings of the Third Workshop on Speech and Language Processing for Assistive Technologies

Can Spanish Be Simpler? LexSiS: Lexical Simplification for Spanish
Stefan Bott | Luz Rello | Biljana Drndarevic | Horacio Saggion
Proceedings of COLING 2012


An Unsupervised Alignment Algorithm for Text Simplification Corpus Construction
Stefan Bott | Horacio Saggion
Proceedings of the Workshop on Monolingual Text-To-Text Generation


A Second-Order Joint Eisner Model for Syntactic and Semantic Dependency Parsing
Xavier Lluís | Stefan Bott | Lluís Màrquez
Proceedings of the Thirteenth Conference on Computational Natural Language Learning (CoNLL 2009): Shared Task


CUCWeb: A Catalan corpus built from the Web
Gemma Boleda | Stefan Bott | Rodrigo Meza | Carlos Castillo | Toni Badia | Vicente López
Proceedings of the 2nd International Workshop on Web as Corpus


CATCG: a general purpose parsing tool applied
Alex Alsina | Toni Badia | Gemma Boleda | Stefan Bott | Àngel Gil | Martí Quixal | Oriol Valentín
Proceedings of the Third International Conference on Language Resources and Evaluation (LREC’02)