Environmental impact assessment (EIA) is the formal process used to predict the environmental consequences of a plan. We present a rule-based extraction system to mine Czech EIA documents. The extraction rules work with a set of documents enriched with morphological information and manually created vocabularies of terms supposed to be extracted from the documents, e.g. basic information about the project (address, ID company, ...), data on the impacts and outcomes (waste substances, endangered species, ...), a final opinion. The documents Notice of Intent contains the section BI2 with the information on the scope (capacity) of the plan.
This toolkit comprises the tools and supporting scripts for unsupervised induction of dependency trees from raw texts or texts with already assigned part-of-speech tags. There are also scripts for simple machine translation based on unsupervised parsing and scripts for minimally supervised parsing into Universal-Dependencies style.
Source code of the first full and running version for the Malach Center User Interface, does not contain data or metadata fo the digital objects and resources.
This tool is the first morphological analyzer ever for this language.
The analyzer is a FST that produces all possible segmentations and tagging sequences in a word-by-word fashion.
Omorfi is free and open source project containing various tools and data for handling Finnish texts in a linguistically motivated manner. The main components of this repository are:
1) a lexical database containing hundreds of thousands of words (c.f. lexical statistics),
2) a collection of scripts to convert lexical database into formats used by upstream NLP tools (c.f. lexical processing),
3) an autotools setup to build and install (or package, or deploy): the scripts, the database, and simple APIs / convenience processing tools, and
4) a collection of relatively simple APIs for a selection of languages and scripts to apply the NLP tools and access the database
A simple way of browsing CoNLL format files in your terminal. Fast and text-based.
To open a CoNLL file, simply run: ./view_conll sample.conll
The output is piped through less, so you can use less commands to navigate the
file; by default the less searches for sentence beginnings, so you can use "n"
to go to next sentence and "N" to go to previous sentence. Close by "q". Trees
with a high number of non-projective edges may be difficult to read, as I have
not found a good way of displaying them intelligibly.
If you are on Windows and don't have less (but have Python), run like this: python view_conll.py sample.conll
For complete instructions, see the README file.
You need Python 2 to run the viewer.