LTG-internal notes on available data and software resources for the morpho-syntactic analysis of Norwegian text.

• Norsk Ordbank

• OBT

• NorGram

• NDT

• INESS

• UD

• UDPipe

LTG maintains its own copy of NDT in SVN:

  svn co http://svn.emmtee.net/ltg/ndt

Main differences in this version are an organization of the directory and file structure that makes explicit the correspondences between raw text files and the annotated versions. Furthermore FredrikJørgensen has provided a version of the raw texts aligned to the sentence segmentation in the gold standard.

Segmentation of raw, running text into (a) splitting into ‘sentences’ (i.e. root-level utterances) and (b) tokenization into ‘word’-like units. Two to three known de-facto strandards: OBT-style, NorGram-style, and NDT-style.

The mtag tool is the first component in the OBT pipeline and implements sentence spilitting, tokenization, and multi-tagging (morphological analysis). OBT tokens at times comprise multi-words, presumably for ‘words with spaces’ (for eksempel) and maybe for some names?

NDT tokenization (I believe) resembles PTB-style tokens, e.g. splitting at hyphens and slashes. StephanOepen has started to develop an NDT-compatible tokenizer in the REPP framework (through adaptation of PTB-style rules); he would also be interested in using REPP to devise a rule-based sentence splitter. One main advantage of REPP is its output of character offset pointers, which are often useful in applications.

The Punkt implementation in NLTK includes a pre-trained sentence splitting model for Norwegian.

The LAP team has been discussing integration of NorGram parsing, which would most likely make available the NorGram sentence splitter and tokenizer as stand-alone components; however, they require licensing of the proprietary XFST toolkit.

UDPipe implements a classification-based approach to splitting and tokenization and ships with pre-trained models for Norwegian. While the current release of the Norwegian UD treebank lacked information on whitespace boundaries, a forthcoming new version will address this problem.

By morphology we mean all sub-tasks of analyzing word-internal structure, including PoS tagging and lemmatization.