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LtgOslo_DelphinUpdates

StephanOepen edited this page Jul 29, 2013 · 4 revisions

Background

LTG staff actively participates in the informal, multi-national research collaboration on Deep Linguistic Processing with HPSG Initiative (DELPH-IN). At the annual DELPH-IN Summit (i.e. gathering of the clique), partners often give overviews of (more or less) relevant developments at individual sites. This page is intended to develop into a stream of LTG updates related to DELPH-IN.

2013 Site Update

Two funded projects currently use and extend DELPH-IN technologies, WeSearch (on methods for parser adaptation to user-generated content) and LAP (the Language Analysis Portal, part of the Norwegian CLARIN(O) initiative).

Work in WeSearch by AngelinaIvanova (on relating bi-lexical dependency representations and DELPH-IN HPSG analyses), by RebeccaDridan (on, among things, ubertagging for faster and more accurate parsing), and by StephanOepen and off-site collaborators (on working towards documentation of ERG Semantic Analyses) are presented individually at the 2013 Summit.

Another WeSearch activity has been collaborative work with DanFlickinger on enabling the ERG to analyse inputs annotated (optionally) with (two types of) candidate phrase boundaries, or candidate target bi-lexical dependencies. Following are some example inputs (using GML mark-up; see below) that exemplify this functionality:

  She met the ⌊(⌋cat in the hotel.⌊)⌋
  She met the ⌊(⌋cat in the hotel⌊)⌋.
  the cat saw⌊←¦sb-hd⌋ runs.
  the cat saw⌊←¦sb-hd¦<29:34>⌋ runs.

This functionality is not in the 1212 release of the ERG but currently coming together in the ERG trunk; in a first instance, it will be validated in in-house projects at LTG.

In the LAP context, there now is a live pilot portal providing Web access to pre-configured tokenization, PoS tagging, and syntactic dependency parsing tools for English and Norwegian (running on a Norwegian national supercomputer, i.e. potentially making available high-performance computing capabilities to non-technical users). The LAP architecture is based on the LAF (Linguistic Annotation Framework) data model, but using a distributed NoSQL database as the annotation store, where components record and retrieve annotatons from earlier components in complex workflows. In the year to come, it is expected that the core DELPH-IN toolchain will be made available through the LAP.

Finally, two

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