@conference {6366,
	title = {Improving a symbolic parser through partially supervised learning},
	booktitle = {The 13th International Conference on Parsing Technologies (IWPT)},
	year = {2013},
	address = {Nara, Japon},
	abstract = {Recently, several statistical parsers have been trained and evaluated on the dependency version of the French TreeBank (FTB). However, older symbolic parsers still exist, including FRMG, a wide coverage TAG parser. It is interesting to compare these different parsers, based on very different approaches, and explore the possibilities of hybridization. In particular, we explore the use of partially supervised learning techniques to improve the performances of FRMG to the levels reached by the statistical parsers.
},
	keywords = {parsing, partially supervised machine learning, statitistical parsing, symbolic parsing, Tree Adjoining Grammar},
	url = {http://hal.inria.fr/hal-00879358},
	author = {Villemonte De La Clergerie, {\'E}ric}
}
@conference {6369,
	title = {Building factorized TAGs with meta-grammars},
	booktitle = {The 10th International Conference on Tree Adjoining Grammars and Related Formalisms - TAG+10},
	year = {2010},
	address = {New Haven, CO, {\'E}tats-Unis},
	abstract = {Highly compacted TAGs may be built by allowing subtree factorization operators within the elementary trees. While hand-crafting such trees remains possible, a better option arises from a coupling with meta-grammar descriptions. The approach has been validated by the development of FRMG, a wide-coverage French TAG of only 207 trees.
},
	keywords = {metagrammar, NLP, parsing, TAG},
	url = {http://hal.inria.fr/inria-00551974},
	author = {Villemonte De La Clergerie, {\'E}ric}
}
@conference {6371,
	title = {FRMG: {\'e}volutions d{\textquoteright}un analyseur syntaxique TAG du fran{\c c}ais},
	booktitle = {Journ{\'e}e de l{\textquoteright}ATALA sur : Quels analyseurs syntaxiques pour le fran{\c c}ais ?},
	year = {2009},
	publisher = {ATALA},
	organization = {ATALA},
	address = {Paris, France},
	abstract = {Nous pr{\'e}sentons FRMG, un analyseur syntaxique du fran{\c c}ais {\`a} large couverture. Nous mettons en avant les m{\'e}thodes qui ont permis d{\textquoteright}am{\'e}liorer ses performances depuis sa naissance, en 2004, initi{\'e}e dans le cadre de la premi{\`e}re campagne EASy d{\textquoteright}{\'e}valuation des analyseurs syntaxiques
},
	keywords = {Grammar, NLP, parsing, TAG},
	url = {http://hal.inria.fr/inria-00553260},
	author = {de La Clergerie, {\'E}ric and Sagot, Beno{\^\i}t and Nicolas, Lionel and Gu{\'e}not, Marie-Laure},
	editor = {de La Clergerie, {\'E}ric and Paroubek, Patrick}
}
