GrailLight

©️ 2015-2026 CNRS

©️ 2015-2026 Richard Moot (@RichardMoot)

Grail Light is a light-weight chart parser for multimodal type-logical
grammars, written in SWI Prolog. It is accompanied by a set of auxiliary tools for interaction with the
supertagger, interactive parsing, corpus extraction, etc.

Together with DeepGrail, or the older DeepGrail2021, Grail Light
can function as a wide-coverage parser for French, assigning Discourse Representation Structures as the meaning of parsed sentences. Grail Light produces natural
deduction proofs like those found in the TLGbank and uses the same conventions for formulas, rules and proofs.

There is a separte page describing command line usage of the chart parser with an external supertagger. Command line usage is recommended for practical applications.

Quick Start

Clone the repository, enter the Grail Light directory, start SWI
Prolog then type.

[grail_light_cr,annodis].

This will load Grail Light as well as the sentences from the Annodis
corpus.

To parse a sentence, type

sentence(2, Semantics).

This will parse the sentence and unify Semantics with the meaning
computed for this sentence.

LaTeX Output

A successful parse will produce a LaTeX representation both of the
proof found and of the meaning. To see the LaTeX output, type the
following (in a shell terminal).

pdflatex latex_proofs.tex

User interface to the part-of-speech/supertagger

Use the file DeepGrail.tcl for a TclTk user interface to the part-of-speech tagger and supertagger. You can select either the DeepGrail Transformer supertagger (strongly recommended) or the older Keras LSTM taggers and models from DeepGrail. Be sure to set the deepgrail_prefix variable in the file to the path containing the predict.py script from DeepGrail.

You can then simply run DeepGrail.tcl and type an input sentence into the entry field. The result of the supertagger looks as shown in the figure below.

In each case, the darker part of the bar (next to each formula) indicates the probability assigned by the supertagger to the formula (moving the mouse pointer over a formula displays the formula and its probability).

The result of the supertagger is passed as input to GrailLight, and if a proof is found, the syntactic proof can be found be selecting Proof from the File menu, and the meaning (in Discourse Representation Theory) can be found by selecting Semantics from the File menu.

The menu allows you the change the supertagger/models used and the beta value of the supertagger; essentially, larger beta values result in more formulas per word, meaning slower parsing but higher likelyhood of finding a proof. It is recommended to use a fairly high beta value (such as the default 0.1) and only decrease it when no proof is found. Several useful values are available in the Beta item of the Options menu.

User interface to the chart parser

Type make parser.tcl and start the created file parser.tcl to open a rudimentary TclTk interface to the chart parser. Example input files for the parser can be found in the chart_proofs/aux directory of the TLGbank. Giving parser.tcl a file as argument will open a Prolog file containing parser input. You can also load a file by selecting Load from the File menu or try.

head -364 annodis.pl > anno10.pl
./parser.tcl anno10.pl

to manually parse the first 10 sentences of the annodis.pl file in the repository (you can do this for the complete file as well, but this requires a quite a bit of patience reading all data).

After startup, the parser window looks as follows, changing with the input sentence and the parser actions performed.

Each table row displays the current structure, formula, log probability, and stack information of the active items in the chart (read chart_parser.pdf for more information about the chart parser).

You can double-click on table row to apply a chart rule to this item. When there are multiple possibilities, a pop-up allows you to select the desired one (with <Enter>). You can undo a choice by pressing <u>, and export the parser result by pressing x.

User interface for manually annotating and correcting additional sentences

The file treebank_annotator.tcl is another interface to the part-of-speech tagger and supertagger. Contrary to the Supertag.tcl script, this script is useful for manually annotating additional data, bootstrapping with the current output of the taggers, and manually correcting the errors, first of the part-of-speech tags, then of the supertags.

Going Further

The file readme.pdf contains more detailed instructions whereas the
file chart_parser.pdf describes the strategy used by the chart parser.

Acknowledgments

This chart parser has been developed starting from source code
originally developed by Shieber e.a. (1995), though with a set of
inference rules and a number of improvements which I specifically tailored for multimodal type-logical grammars.

The Prolog file lefff.pl has been automatically extracted from the
Lefff lexicon (Sagot, 2010).

The file annodis.pl has been extracted from the
Sequoia corpus (Candito and Seddah,
2012) and is part of the TLGbank
(Moot, 2015).

References

Marie Candito and Djamé Seddah (2012) Le corpus Sequoia : annotation
syntaxique et exploitation pour l’adaptation d’analyseur par pont
lexical, Proceedings TALN'2012, Grenoble, France.

Richard Moot (2015) A Type-Logical Treebank for French, Journal of
Language Modelling 3(1), pp. 229-265.

Richard Moot (2017) The Grail Theorem Prover: Type Theory for Syntax and Semantics. In Stergios Chatzikyriakidis and Zhaohui Luo (eds.) Modern Perspectives in
Type-Theoretical Semantics, pp. 247-277.

Richard Moot (2021) Type-logical investigations: proof-theoretic, computational and linguistic aspects of modern type-logical grammars (Habilitation à Diriger des Recherches, Université Montpellier).

Benoît Sagot (2010) The Lefff, a freely available and large-coverage morphological and syntactic lexicon for French. In Proceedings of the 7th international conference on Language Resources and Evaluation (LREC 2010), Istanbul, Turkey

Stuart M. Shieber, Yves Schabes and Fernando C. N. Pereira (1995)
Principles and Implementation of Deductive Parsing, Journal of
Logic Programming 24(1-2), pp. 3-36.