prove_SICK_NL

Prove Ducth NLI problems of SICK-NL with LangPro. Note that the current repo contains SICK-NL version that corresponds its English counterpart used for Semeval-2014 Task 1. SemeEval version contains in total 9927 problems while the original one 9840 problems.

Prerequisites

The current repo and the LangPro repo shoudl be in the same directory.

Get Langpro repo with git clone --branch nl [email protected]:kovvalsky/LangPro.git or git clone --branch nl https://github.com/kovvalsky/LangPro.git. It is used for theorem-proving and converting type-logical terms into simply-typed terms. ⚠️ It is important to select nl branch. Additionally add --single-branch if you want to clone only nl branch.

produce.ini contains rules how to generate files. You will need to install produce if you want to use the rules to build files from scratch.

HowTo

Theorem proving SICK-NL problems

Before proving the problems, either enter the prolog interactive mode (recommended for a demo usage):

% loading the prover with alpino (or npn_robbert) trees
$ swipl -f prolog/main.pl  SICK_NL/sen.pl  SICK_NL/parses/alpino.pl  WNProlog/wn.pl
% This can be run only in the beginning, to set the global parameters: the part of the dataset, language flag, lexical annotation file, and theorem proving parameters
?- parList([parts([train]), lang(nl), anno_json('SICK_NL/anno/alpino.json'), complete_tree, allInt, aall, wn_ant, wn_sim, wn_der, constchck]).

Or run the prolog goals directly from the terminal:

$ swipl -g "PROLOG_PREDICATES_TO_BE_CHECKED" -t halt -f prolog/main.pl  SICK_NL/sen.pl  SICK_NL/parses/alpino.pl  WNProlog/wn.pl

Prove a particular problem without abductive training

% In an interactive mode, prove a problem and pretty display the proof in a separate window
% Run LangPro in the graphical mode with aligned terms (if the prove is found, it is most probably done with aligned terms as this mode is tested first for efficiency reasons.)
?- gentail(aligned, 8502).
Tableau for "yes" checking is generated with Ter,6 ruleapps
XP: [isa(man,persoon),isa(meer,water)]
true.

An image of the proof:

# The same but with a terminal command:
$ swipl -g "parList([parts([train]), lang(nl), anno_json('SICK_NL/anno/alpino.json'), complete_tree, allInt, aall, wn_ant, wn_sim, wn_der, constchck]), gentail(aligned, 8502)." -f prolog/main.pl  SICK_NL/sen.pl  SICK_NL/parses/alpino.pl  WNProlog/wn.pl

Check LangPro repo for running the prover for entire data split.

Generate typed terms in LaTeX/PDF

For all sentences filtered with a label or a part

The rule uses the corresponding json annotation file and parse terms from a parser (npn_robbert or alpino) to obtain annotated simply-typed terms and format them in LateX. The trial part keeps only those terms whose sentences occur in the TRIAL part of SICK. Usually it is good to use a filter otherwise files tend to be >15MB and its later compilation into PDF will take long time. Other options for filter are yes (problems with entailment label), no (problems with contradiction label), unknown (problems with neutral label), train, test, and all (i.e. no filters).

produce -d -f produce.ini  SICK_NL/latex/npn.spacy_sm.trial.tex

If you want additionally to tex file to create pdf from it, run:

produce -d -f produce.ini  SICK_NL/latex/npn.spacy_sm.trial.pdf

The conversion uses lualatex as it is faster than pdflatex and can deal with huge files (well, at least on my machine:)).

For a specific NLI problem

Create a pdf that depicts how initial trees are converted into the final trees for the sentences of an NLI problem with a specific ID (e.g., 1333).

produce -d -b -f produce.ini   SICK_NL/latex/npn.spacy_lg.1333.pdf