Legal Text Analysis Project: Leveraging NLP for Enhanced Understanding and Insight

 A key point in the development of NLP solutions is the consideration of language proficiency. The terms and jargon used in specialized sectors, such as the medical sector, differ greatly from those used in the financial sector, which in turn are not comparable to those in the legal sector.

The legal texts contain a series of specifications such as:
The breadth of the domain in terms of textual typology.
The variety of target groups.
The linguistic features of the domain.
Furthermore, in the latter case, not only is the legal terminology of the domain covered, but it also tends to co-occur with terminologies from all areas.

The limited number of NLP resources and tools tailored to the overall domain.
The predominance of English, since most of the resources and tools available are developed for processing texts in English.
A slowed adoption of smart technologies in the legal and administrative sector compared to other sectors such as the biomedical or financial sector.
The heterogeneity of formats in which the data is found. For example, the data may contain text, images or recordings, such as in the case of court hearings. This implies the need to apply different techniques to process the different formats.

Some of the tasks used in legal texts are:


The applied methodology has evolved in recent years. Abdallah et al. (2023) and Dias and Santos (2022) compared traditional vs modern methods in NLP. Traditional include rule-based and information retrieval methods. Modern methods include deep learning with RNN and LSTMs, and transformers such as BERT.



Nowadays, neural networks with Transforms and LLMs are applied. 




Katz et al. (2023) made a review of papers related with NLP and legal texts. English is the most common language applied. 

Some of the papers most cited in this field are:


At the Spanish national level, some recent initiatives have appeared. In December 2019, and in order to promote the development of NLP resources and tools in the legal domain in Spanish, the “IberLegal” conference was organized, within the framework of the activities of the Spanish Language Technologies Plan (TL Plan). The conference covered a range of topics of interest, such as the extraction of legal terminology, intelligent searches in documents and retrieval of legal information, tools to assist citizens in writing texts for public administration and, finally , temporal expressions in legal texts (PlanTL, 2019).

Along the same lines, in 2020 the “LT4Gov” workshop was organized within the framework of the international conference LREC 2020 (Language Resources and Evaluation Conference). The workshop focused on studies and initiatives that address the use of language technologies in the field of public administration and government entities.

In recent years, an effort has been made to create models in the legal field with texts in Spanish. Some of the most notable include the creation of corpora such as LEGAL-ES (link), RoBERTalex (link), LegalBETO (link) or Narralegal (link). 

Other resources in spanish:

https://github.com/PlanTL-GOB-ES/lm-legal-es

Plan TL developed a model called roBERTalex that is based on BERT. 







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