Automatic Assignment of Section Structure to Texts of Dutch Court Judgments
| Authors |
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|---|---|
| Publication date | 2016 |
| Host editors |
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| Book title | Legal Knowledge and Information Systems |
| Book subtitle | JURIX 2016: The Twenty-Ninth Annual Conference |
| ISBN |
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| ISBN (electronic) |
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| Series | Frontiers in Artificial Intelligence and Applications |
| Event | JURIX 2016: 29th Annual Conference |
| Pages (from-to) | 167-172 |
| Number of pages | 6 |
| Publisher | Amsterdam: IOS Press |
| Organisations |
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| Abstract |
A growing number of Dutch court judgments is openly distributed on
Rechtspraak.nl. Currently, many documents are not marked up or marked up only very sparsely, hampering our ability to process these documents automatically. In this paper, we explore the problem of automatic assignment of a section structure to these texts. We experiment with Linear-Chain Conditional Random Fields to label text elements with their roles in the document (text, title or numbering). In this subtask, we report F1 scores of around 0.91 for tagging section titles, and around 1.0 for the other types. Given a list of labels, we experiment with Probabilistic Context-Free Grammars to generate a parse tree which represents the section hierarchy of a document. In this task, we report an F1 score of 0.92. |
| Document type | Conference contribution |
| Language | English |
| Published at | https://doi.org/10.3233/978-1-61499-726-9-167 |
| Downloads |
Automatic Assignment of Section Structure to Texts of Dutch Court Judgments
(Accepted author manuscript)
|
| Permalink to this page | |
