Daniel Bauer


2022

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NLP in Human Rights Research: Extracting Knowledge Graphs about Police and Army Units and Their Commanders
Daniel Bauer | Tom Longley | Yueen Ma | Tony Wilson
Proceedings of the 16th Linguistic Annotation Workshop (LAW-XVI) within LREC2022

In this paper we explore the use of an NLP system to assist the work of Security Force Monitor (SFM). SFM creates data about the organizational structure, command personnel and operations of police, army and other security forces, which assists human rights researchers, journalists and litigators in their work to help identify and bring to account specific units and personnel alleged to have committed abuses of human rights and international criminal law. This paper presents an NLP system that extracts from English language news reports the names of security force units and the biographical details of their personnel, and infers the formal relationship between them. Published alongside this paper are the system’s code and training dataset. We find that the experimental NLP system performs the task at a fair to good level. Its performance is sufficient to justify further development into a live workflow that will give insight into whether its performance translates into savings in time and resource that would make it an effective technical intervention.

2016

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Hyperedge Replacement and Nonprojective Dependency Structures
Daniel Bauer | Owen Rambow
Proceedings of the 12th International Workshop on Tree Adjoining Grammars and Related Formalisms (TAG+12)

2014

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Mapping Between English Strings and Reentrant Semantic Graphs
Fabienne Braune | Daniel Bauer | Kevin Knight
Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14)

We investigate formalisms for capturing the relation between semantic graphs and English strings. Semantic graph corpora have spurred recent interest in graph transduction formalisms, but it is not yet clear whether such formalisms are a good fit for natural language data―in particular, for describing how semantic reentrancies correspond to English pronouns, zero pronouns, reflexives, passives, nominalizations, etc. We introduce a data set that focuses on these problems, we build grammars to capture the graph/string relation in this data, and we evaluate those grammars for conciseness and accuracy.

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Documenting Endangered Languages with the WordsEye Linguistics Tool
Morgan Ulinski | Anusha Balakrishnan | Daniel Bauer | Bob Coyne | Julia Hirschberg | Owen Rambow
Proceedings of the 2014 Workshop on the Use of Computational Methods in the Study of Endangered Languages

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Using Frame Semantics in Natural Language Processing
Apoorv Agarwal | Daniel Bauer | Owen Rambow
Proceedings of Frame Semantics in NLP: A Workshop in Honor of Chuck Fillmore (1929-2014)

2013

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Parsing Graphs with Hyperedge Replacement Grammars
David Chiang | Jacob Andreas | Daniel Bauer | Karl Moritz Hermann | Bevan Jones | Kevin Knight
Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

2012

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Annotation Tools and Knowledge Representation for a Text-To-Scene System
Bob Coyne | Alex Klapheke | Masoud Rouhizadeh | Richard Sproat | Daniel Bauer
Proceedings of COLING 2012

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Semantics-Based Machine Translation with Hyperedge Replacement Grammars
Bevan Jones | Jacob Andreas | Daniel Bauer | Karl Moritz Hermann | Kevin Knight
Proceedings of COLING 2012

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The Dependency-Parsed FrameNet Corpus
Daniel Bauer | Hagen Fürstenau | Owen Rambow
Proceedings of the Eighth International Conference on Language Resources and Evaluation (LREC'12)

When training semantic role labeling systems, the syntax of example sentences is of particular importance. Unfortunately, for the FrameNet annotated sentences, there is no standard parsed version. The integration of the automatic parse of an annotated sentence with its semantic annotation, while conceptually straightforward, is complex in practice. We present a standard dataset that is publicly available and that can be used in future research. This dataset contains parser-generated dependency structures (with POS tags and lemmas) for all FrameNet 1.5 sentences, with nodes automatically associated with FrameNet annotations.

2011

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VigNet: Grounding Language in Graphics using Frame Semantics
Bob Coyne | Daniel Bauer | Owen Rambow
Proceedings of the ACL 2011 Workshop on Relational Models of Semantics

2010

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Sentence Generation as Planning with Probabilistic LTAG
Daniel Bauer | Alexander Koller
Proceedings of the 10th International Workshop on Tree Adjoining Grammar and Related Frameworks (TAG+10)