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Feedback utterances are among the most frequent in dialogue. Feedback is also a crucial aspect of linguistic theories that take social interaction, involving language, into account. This paper introduces the corpora and datasets of a project scrutinizing this kind of feedback utterances in French. We present the genesis of the corpora (for a total of about 16 hours of transcribed and phone force-aligned speech) involved in the project. We introduce the resulting datasets and discuss how they are being used in on-going work with focus on the form-function relationship of conversational feedback. All the corpora created and the datasets produced in the framework of this project will be made available for research purposes.
We present a quantitative approach to disambiguating flat morphological analyses and producing more deeply structured analyses. Based on existing morphological segmentations, possible combinations of resulting word trees for the next level are filtered first by criteria of linguistic plausibility and then by weighting procedures based on the geometric mean. The frequencies for weighting are derived from three different sources (counts of morphs in a lexicon, counts of largest constituents in a lexicon, counts of token frequencies in a corpus) and can be used either to find the best analysis on the level of morphs or on the next higher constituent level. The evaluation shows that for this task corpus-based frequency counts are slightly superior to counts of lexical data.
The task-oriented and format-driven development of corpus query systems has led to the creation of numerous corpus query languages (QLs) that vary strongly in expressiveness and syntax. This is a severe impediment for the interoperability of corpus analysis systems, which lack a common protocol. In this paper, we present KoralQuery, a JSON-LD based general corpus query protocol, aiming to be independent of particular QLs, tasks and corpus formats. In addition to describing the system of types and operations that Koral- Query is built on, we exemplify the representation of corpus queries in the serialized format and illustrate use cases in the KorAP project.
The present thesis introduces KoralQuery, a protocol for the generic representation of queries to linguistic corpora. KoralQuery defines a set of types and operations which serve as abstract representations of linguistic entities and configurations. By combining these types and operations in a nested structure, the protocol may express linguistic structures of arbitrary complexity. It achieves a high degree of neutrality with regard to linguistic theory, as it provides flexible structures that allow for the setting of certain parameters to access several complementing and concurrent sources and layers of annotation on the same textual data. JSON-LD is used as a serialisation format for KoralQuery, which allows for the well-defined and normalised exchange of linguistic queries between query engines to promote their interoperability. The automatic translation of queries issued in any of three supported query languages to such KoralQuery serialisations is the second main contribution of this thesis. By employing the introduced translation module, query engines may also work independently of particular query languages, as their backend technology may rely entirely on the abstract KoralQuery representations of the queries. Thus, query engines may provide support for several query languages at once without any additional overhead. The original idea of a general format for the representation of linguistic queries comes from an initiative called Corpus Query Lingua Franca (CQLF), whose theoretic backbone and practical considerations are outlined in the first part of this thesis. This part also includes a brief survey of three typologically different corpus query languages, thus demonstrating their wide variety of features and defining the minimal target space of linguistic types and operations to be covered by KoralQuery.
Contents:
1. Michal Křen: Recent Developments in the Czech National Corpus, S. 1
2. Dan Tufiş, Verginica Barbu Mititelu, Elena Irimia, Stefan Dumitrescu, Tiberiu Boros, Horia Nicolai Teodorescu: CoRoLa Starts Blooming – An update on the Reference Corpus of Contemporary Romanian Language, S. 5
3. Sebastian Buschjäger, Lukas Pfahler, Katharina Morik: Discovering Subtle Word Relations in Large German Corpora, S. 11
4. Johannes Graën, Simon Clematide: Challenges in the Alignment, Management and Exploitation of Large and Richly Annotated Multi-Parallel Corpora, S. 15
5. Stefan Evert, Andrew Hardie: Ziggurat: A new data model and indexing format for large annotated text corpora, S. 21
6. Roland Schäfer: Processing and querying large web corpora with the COW14 architecture, S. 28
7. Jochen Tiepmar: Release of the MySQL-based implementation of the CTS protocol, S. 35