# GrailLight

:copyright: 2015-2020 [CNRS](http://www.cnrs.fr)

:copyright: 2015-2020 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](https://richardmoot.github.io/DeepGrail/) or the older [part-of-speech tag and supertag models](https://github.com/RichardMoot/models), 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](http://richardmoot.github.io/TLGbank/) and uses the same conventions for formulas, rules and proofs.

# 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 `Supertag.tcl` for a TclTk user interface to the part-of-speech tagger and supertagger. You can select either the Keras LSTM taggers and models from [DeepGrail](https://richardmoot.github.io/DeepGrail/) (recommended, set the `keras_tagger_prefix` and `keras_model_prefix` in `Supertag.tcl` to the executables and models respectively) or the [Clark and Curran taggers](https://www.aclweb.org/anthology/J07-4004.pdf) with the corresponding [French models](https://github.com/RichardMoot/models) (set the `cnc_tagger_prefix` and `model_prefix` variables in `Supertag.tcl` to the executables and models respectively).

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

![screen shot of the interactive interface to the taggers](supertagger.png)

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](http://richardmoot.github.io/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.

![screen shot of the interactive interface to the chart parser](parser.png)

Each table row displays the current structure, formula, log probability, and stack information of the active items in the chart (read [`chart_parser.pdf`](https://github.com/RichardMoot/GrailLight/blob/master/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`](https://github.com/RichardMoot/GrailLight/blob/master/readme.pdf) contains more detailed instructions whereas the
file [`chart_parser.pdf`](https://github.com/RichardMoot/GrailLight/blob/master/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](http://alpage.inria.fr/~sagot/lefff.html) (Sagot, 2010).

The file `annodis.pl` has been extracted from the
[Sequoia corpus](http://deep-sequoia.inria.fr) (Candito and Seddah,
2012) and is part of the [TLGbank](http:richardmoot.github.io/TLGbank)
(Moot, 2015).

# References

Marie Candito and Djam&eacute; 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.

Beno&icirc;t 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.