Sold by: Instituto Ingenieria ConocimientoÂ
Deployed on AWS
ClauseMapper is a clause classifier for contracts in Spanish. This classifier analyzes the contract text and identifies the segments of information related up to 15 types of different clauses.
Overview
With extensive experience in developing natural language processing (NLP) products and services in Spanish, from the Instituto de Ingenieria del Conocimiento (IIC), we want to share our knowledge with the rest of the world by making available the best NLP assets in our language. ClauseMapper is a clause classifier for contracts in Spanish. This classifier analyzes the contract text and identifies the segments of information related up to 15 types of clauses, namely:
object (objeto), contract termination (resolucion), contract duration (duracion), guarantee (garantia economica), contract price (precio del contrato), delay penalty (penalidad por demora), confidentiality (confidencialidad), defective performance penalty (penalidad por cumplimiento defectuoso), verification of contract compliance (verificacion del cumplimiento), personal data protection (proteccion de datos personales), damage award (indemnizacion de danos y perjuicios por incumplimiento), warranty duration (plazo de garantia), bank guarantee (garantia - aval bancario), third-party damage compensation (indemnizacion de danos a terceros), and price retention guarantee (retencion del precio)It uses a NLU machine learning model to automatically segment and tag information. ClauseMapper goal is twofold: on the one hand, it can be used by specialists in the legal sector, minimizing contract review time and effort, and on the other hand, it can help non-professionals in the legal industry to better understand the information in a contract. ClauseMapper is specifically designed to process Spanish contracts written in Spanish.
This work has received funding from the Inesdata-project (Infrastructure to Investigate Data Spaces in Distributed Environments at UPM), a project funded under the UNICO I+D CLOUD call by the Ministry for Digital Transformation and the Civil Service, in the framework of the recovery plan PRTR financed by the European Union (NextGenerationEU). Project code: TSI-063100-2022-0001
Highlights
- How long is your rental? What penalties apply for breakdowns? When can you cancel your gas contract? All these everyday questions are usually answered by consulting the respective contracts. However, it is not always easy to locate information in legal texts. ClauseMapper facilitates access to the information contained in the different clauses. It analyzes the content and labels it to help users focus their attention on the contracts key aspects.
- ClauseMapper is designed for Spanish. ClauseMapper is based on a dataset called 3CEL, and a NLU machine learning model called MEL. Check Aldama et al (2025) (https://arxiv.org/abs/2501.15990) for more information about the dataset. Check Betancur et al (2025) (https://arxiv.org/abs/2501.16011) for more infromation about the model.
- Contract clause extractor and classifier for Spanish contracts.
Details
Delivery method
Latest version
Deployed on AWS
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Dimension | Description | Cost |
|---|---|---|
ml.c5.2xlarge Inference (Batch) Recommended | Model inference on the ml.c5.2xlarge instance type, batch mode | $2.76/host/hour |
inference.count.m.i.c Inference Pricing | inference.count.m.i.c Inference Pricing | $0.10/request |
ml.c6i.large Inference (Batch) | Model inference on the ml.c6i.large instance type, batch mode | $5.52/host/hour |
ml.m5.large Inference (Batch) | Model inference on the ml.m5.large instance type, batch mode | $1.38/host/hour |
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Delivery details
Amazon SageMaker model
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Version release notes
This is the first version of ClauseMapper. This initial release demonstrates our commitment to making Spanish machine learning resources. While this is just the beginning, we are excited about the potential applications and improvements that future iterations will bring. We look forward to refining and enhancing our classifier based on user feedback and continued research.
Additional details
Inputs
- Summary
The analyzer accepts a JSON that conforms to the following format:
- A single text
https://github.com/iiconocimiento/iic-aws/blob/main/notebooks/clausemapper/data/input/input.json
https://github.com/iiconocimiento/iic-aws/blob/main/notebooks/clausemapper/data/input/input.json
Input data descriptions
The following table describes supported input data fields for real-time inference and batch transform.
Field name | Description | Constraints | Required |
|---|---|---|---|
text | A JSON object containing the text to analyze. | - | Yes |
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