Datasets:

BSC-LT
/

rpaweb

id string	language string	intent string	step int32	input string	requirements string	outputs string	anonymized_data string	json_data string	html_data string
i01.en.0001	en	accessing the register	0	I need access to the vehicle register	"{\"*accés: \\n- sense especificar (SE)\\n- dades (DA): \\n - DA: SE\\n - DA: especificant\(...TRUNCATED)	"{\"classe\": \"AccedirPadro\", \"nif\": \"94062603D\", \"nom\": \"Elvira\", \"primer-cognom\": \"Co(...TRUNCATED)	"{\"nif\": \"94062603D\", \"nom\": \"Elvira\", \"primer-cognom\": \"Collado\", \"segon-cognom\": \"S(...TRUNCATED)	"{\"browserCode\": \"{\\\"name\\\":\\\"click\\\",\\\"selector\\\":\\\"internal:role=link[name=\\\\\\(...TRUNCATED)	"<!DOCTYPE html><html xml:lang=\"ca-ES\" lang=\"ca-ES\"><head><script type=\"text/javascript\" id=\"(...TRUNCATED)
i01.en.0001	en	accessing the register	1	I need access to the vehicle register	"{\"*accés: \\n- sense especificar (SE)\\n- dades (DA): \\n - DA: SE\\n - DA: especificant\(...TRUNCATED)	"{\"classe\": \"AccedirPadro\", \"nif\": \"94062603D\", \"nom\": \"Elvira\", \"primer-cognom\": \"Co(...TRUNCATED)	"{\"nif\": \"94062603D\", \"nom\": \"Elvira\", \"primer-cognom\": \"Collado\", \"segon-cognom\": \"S(...TRUNCATED)	"{\"agentFocus\": \"getByText('Accés amb NIF i matrícula Acc')\", \"userFeedback\": \"Through my N(...TRUNCATED)	"<!DOCTYPE html><html xml:lang=\"ca-ES\" lang=\"ca-ES\"><head>\n<meta charset=\"UTF-8\">\n<meta http(...TRUNCATED)
i01.en.0001	en	accessing the register	2	I need access to the vehicle register	"{\"*accés: \\n- sense especificar (SE)\\n- dades (DA): \\n - DA: SE\\n - DA: especificant\(...TRUNCATED)	"{\"classe\": \"AccedirPadro\", \"nif\": \"94062603D\", \"nom\": \"Elvira\", \"primer-cognom\": \"Co(...TRUNCATED)	"{\"nif\": \"94062603D\", \"nom\": \"Elvira\", \"primer-cognom\": \"Collado\", \"segon-cognom\": \"S(...TRUNCATED)	"{\"agentFocus\": \"getByLabel('Codi *')\", \"userFeedback\": \"428460\", \"userRequest\": \"Can i h(...TRUNCATED)	"<!DOCTYPE html><html class=\"atc_integracio\" xml:lang=\"ca-ES\" lang=\"ca-ES\"><!-- Mirrored from (...TRUNCATED)
i01.en.0001	en	accessing the register	3	I need access to the vehicle register	"{\"*accés: \\n- sense especificar (SE)\\n- dades (DA): \\n - DA: SE\\n - DA: especificant\(...TRUNCATED)	"{\"classe\": \"AccedirPadro\", \"nif\": \"94062603D\", \"nom\": \"Elvira\", \"primer-cognom\": \"Co(...TRUNCATED)	"{\"nif\": \"94062603D\", \"nom\": \"Elvira\", \"primer-cognom\": \"Collado\", \"segon-cognom\": \"S(...TRUNCATED)	"{\"browserCode\": \"{\\\"name\\\":\\\"fill\\\",\\\"selector\\\":\\\"internal:label=\\\\\\\"Codi *\\(...TRUNCATED)	"<!DOCTYPE html><html class=\"atc_integracio\" xml:lang=\"ca-ES\" lang=\"ca-ES\"><!-- Mirrored from (...TRUNCATED)
i01.en.0001	en	accessing the register	4	I need access to the vehicle register	"{\"*accés: \\n- sense especificar (SE)\\n- dades (DA): \\n - DA: SE\\n - DA: especificant\(...TRUNCATED)	"{\"classe\": \"AccedirPadro\", \"nif\": \"94062603D\", \"nom\": \"Elvira\", \"primer-cognom\": \"Co(...TRUNCATED)	"{\"nif\": \"94062603D\", \"nom\": \"Elvira\", \"primer-cognom\": \"Collado\", \"segon-cognom\": \"S(...TRUNCATED)	"{\"browserCode\": \"{\\\"name\\\":\\\"click\\\",\\\"selector\\\":\\\"internal:label=\\\\\\\"No soc (...TRUNCATED)	"<!DOCTYPE html><html class=\"atc_integracio\" xml:lang=\"ca-ES\" lang=\"ca-ES\"><!-- Mirrored from (...TRUNCATED)
i01.en.0001	en	accessing the register	5	I need access to the vehicle register	"{\"*accés: \\n- sense especificar (SE)\\n- dades (DA): \\n - DA: SE\\n - DA: especificant\(...TRUNCATED)	"{\"classe\": \"AccedirPadro\", \"nif\": \"94062603D\", \"nom\": \"Elvira\", \"primer-cognom\": \"Co(...TRUNCATED)	"{\"nif\": \"94062603D\", \"nom\": \"Elvira\", \"primer-cognom\": \"Collado\", \"segon-cognom\": \"S(...TRUNCATED)	"{\"agentFocus\": \"locator('iframe[name=\\\"c-3ciaa21ijlo\\\"]').contentFrame().locator('tr:nth-chi(...TRUNCATED)	"<!DOCTYPE html><html class=\"atc_integracio\" xml:lang=\"ca-ES\" lang=\"ca-ES\"><!-- Mirrored from (...TRUNCATED)
i01.en.0001	en	accessing the register	6	I need access to the vehicle register	"{\"*accés: \\n- sense especificar (SE)\\n- dades (DA): \\n - DA: SE\\n - DA: especificant\(...TRUNCATED)	"{\"classe\": \"AccedirPadro\", \"nif\": \"94062603D\", \"nom\": \"Elvira\", \"primer-cognom\": \"Co(...TRUNCATED)	"{\"nif\": \"94062603D\", \"nom\": \"Elvira\", \"primer-cognom\": \"Collado\", \"segon-cognom\": \"S(...TRUNCATED)	"{\"browserCode\": \"{\\\"name\\\":\\\"click\\\",\\\"selector\\\":\\\"internal:role=button[name=\\\\(...TRUNCATED)	"<!DOCTYPE html><html class=\"atc_integracio\" xml:lang=\"ca-ES\" lang=\"ca-ES\"><!-- Mirrored from (...TRUNCATED)
i01.en.0001	en	accessing the register	7	I need access to the vehicle register	"{\"*accés: \\n- sense especificar (SE)\\n- dades (DA): \\n - DA: SE\\n - DA: especificant\(...TRUNCATED)	"{\"classe\": \"AccedirPadro\", \"nif\": \"94062603D\", \"nom\": \"Elvira\", \"primer-cognom\": \"Co(...TRUNCATED)	"{\"nif\": \"94062603D\", \"nom\": \"Elvira\", \"primer-cognom\": \"Collado\", \"segon-cognom\": \"S(...TRUNCATED)	{"trace_finish": true}	"<!DOCTYPE html><html class=\"atc_integracio\" xml:lang=\"ca-ES\" lang=\"ca-ES\"><!-- Mirrored from (...TRUNCATED)
i01.en.0001	en	accessing the register	8	I need access to the vehicle register	"{\"*accés: \\n- sense especificar (SE)\\n- dades (DA): \\n - DA: SE\\n - DA: especificant\(...TRUNCATED)	"{\"classe\": \"AccedirPadro\", \"nif\": \"94062603D\", \"nom\": \"Elvira\", \"primer-cognom\": \"Co(...TRUNCATED)	"{\"nif\": \"94062603D\", \"nom\": \"Elvira\", \"primer-cognom\": \"Collado\", \"segon-cognom\": \"S(...TRUNCATED)	"{\"browserCode\": \"{\\\"name\\\":\\\"click\\\",\\\"selector\\\":\\\"internal:role=link[name=\\\\\\(...TRUNCATED)	"<!DOCTYPE html><html xml:lang=\"ca-ES\" lang=\"ca-ES\"><head>\n<meta charset=\"UTF-8\">\n<meta http(...TRUNCATED)
i01.en.0001	en	accessing the register	9	I need access to the vehicle register	"{\"*accés: \\n- sense especificar (SE)\\n- dades (DA): \\n - DA: SE\\n - DA: especificant\(...TRUNCATED)	"{\"classe\": \"AccedirPadro\", \"nif\": \"94062603D\", \"nom\": \"Elvira\", \"primer-cognom\": \"Co(...TRUNCATED)	"{\"nif\": \"94062603D\", \"nom\": \"Elvira\", \"primer-cognom\": \"Collado\", \"segon-cognom\": \"S(...TRUNCATED)	"{\"agentFocus\": \"getByLabel('NIF *')\", \"userFeedback\": \"94062603D\", \"userRequest\": \"Can i(...TRUNCATED)	"<!DOCTYPE html><html class=\"atc_integracio\" xml:lang=\"ca-ES\" lang=\"ca-ES\"><!-- Mirrored from (...TRUNCATED)

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Dataset Card for rpaweb

The rpaweb dataset contains multilingual annotations of Robotic Process Automation (RPA) actions in a web environment in English, Spanish and Catalan.
It has been designed to train multimodal models capable of autonomously performing browser-based tasks based on natural language user requests.

The corpus documents each user request along with the full sequence of web automation actions needed to fulfil it, including structured JSON code, natural language descriptions, web page screenshots, and HTML dumps.

The dataset covers five main usage scenarios, each divided into 15 intents in total:

Agència Tributària de la Generalitat de Catalunya: Vehicle CO₂ tax procedures. Accessing, consulting, modifying vehicle records, reporting status changes, etc.
Agencia Tributaria del Gobierno de España: Personal finance procedures. Booking appointments, checking tax status.
Aladí - Xarxa de Biblioteques Municipals de la Diputació de Barcelona: Book queries.
TimeOut: Search and browse city activities and events.
Trello: Project management actions with boards, lists, cards.

Dataset Details

Curated by: Barcelona Supercomputing Center (BSC)
Funded by: AINA
Languages: Catalan (ca), English (en), Spanish (es)
License: CC BY 4.0

Uses

Direct Use

Training and evaluating multimodal RPA agents.
Research on grounding natural language instructions into executable browser actions.
Studying multilingual RPA workflows.

Out-of-Scope Use

Not intended for processing or generating real personal data.
Not designed for high-stakes automation without human oversight.

Dataset Structure

The dataset has a single split (train) for each of the 3 language subsets (en, es, ca) and includes the following fields per action:

id: Unique action identifier which consists of {intent_id}.{lang}.{action_id}
language: Language of the action.
intent: Natural language description of the action.
step: Step of the action input.
input: User request text in natural language.
requirements: Set of preconditions or input parameters needed before executing the RPA workflow for a given user request.
outputs: The expected result(s) or goal state after executing the RPA workflow.
anonymized_data: A mapping of personal data elements detected during annotation to synthetic placeholder values.
png_file: PNG screenshot of the web page before execution.
json_data: JSON code of the RPA step.
html_data: HTML dump of the web page before execution.

The default format of the dataset is a JSONL file, where each line has the following structure:

{"id": "i11.en.0015",
 "language": "en",
 "intent": "saving/emailing a bibliographic record",
 "step": 7,
 "input": "Save the books’ information",
 "requirements": "{\"*Com guardar registres: enviar com a fitxer o a correu?\": \"FITXER\", \"*S'especifica com guarder els registres?\": \"NO\", \"*S'especifica l'adreça d'email?\": \"no rellevant\", \"*S'especifica el títol de l'email?\": \"no rellevant\", \"*format del registre:- Visualització completa (TOT)- Visualització breu (BREU)- MARC\": \"MARC\", \"*S’especifica el format del registre?\": \"NO\"}",
 "outputs": "{\"classe\": \"GuardarEnviarRegistreBibliografic\", \"email\": \"no rellevant\", \"assumpte\": \"no rellevant\"}",
 "anonymized_data": "{}",
 "png_file": "data/en/i11.en.0015.7.png",
 "json_data": "{\"browserCode\": \"{\\\"name\\\":\\\"click\\\",\\\"selector\\\":\\\"internal:role=button[name=\\\\\\\"Submit\\\\\\\"i]\\\",\\\"signals\\\":[{\\\"name\\\":\\\"download\\\",\\\"downloadAlias\\\":\\\"2\\\"}],\\\"button\\\":\\\"left\\\",\\\"modifiers\\\":0,\\\"clickCount\\\":1,\\\"pageAlias\\\":\\\"page\\\",\\\"locator\\\":{\\\"kind\\\":\\\"role\\\",\\\"body\\\":\\\"button\\\",\\\"options\\\":{\\\"attrs\\\":[],\\\"exact\\\":false,\\\"name\\\":\\\"Submit\\\"}}}\\n\", \"nlpDescription\": \"submit\", \"subintent\": \"browser_action\"}",
 "html_data": "<!DOCTYPE html><html lang=\"en\"><head><meta http-equiv=\"X-UA-Compatible\" content=\"IE=edge\">\n\n<title>Diputació de Barcelona [...]""
}

The source files consist of:

peticions_usuari/: CSV files with user requests, parameters, and anonymized personal data placeholders.
accions_rpa/: directories per request containing JSON, PNG, HTML, and anonymization mapping.

Dataset Creation

Curation Rationale

The rpaweb dataset was developed to support research and development of multilingual, multimodal systems capable of performing Robotic Process Automation (RPA) actions in web environments.
Its main objective is to connect natural language understanding with structured browser automation, enabling models to convert user requests into reproducible, executable workflows.
The dataset includes a broad range of domains—government services, library catalog searches, event listings, and project management platforms—to ensure coverage of diverse interaction patterns and action types.

Source Data

Data Collection and Processing

The dataset content was produced through a controlled, tool-assisted annotation workflow:

User request creation
- Requests were manually authored for each intent in Catalan (ca), English (en), and Spanish (es).
- Each language’s dataset was generated independently (not translations) to maximize linguistic and phrasing diversity.
- Relevant parameters (e.g., year, license plate, search terms) were explicitly annotated for each request.
Execution environment
- Annotators used a dedicated RPA annotation tool integrated with the Playwright automation framework.
- All actions were executed on live websites or simulated environments corresponding to the target intent.
Annotation outputs
- Each user request was paired with a sequence of action quadruples:
  1. JSON code representing the RPA command.
  2. Natural language description of the action.
  3. PNG screenshot of the webpage before action execution.
  4. HTML dump of the webpage before action execution.
Validation
- Automated checks ensured JSON validity, action type correctness, and anonymization completeness.
- Manual inspection of sampled data validated task flow consistency.

Who are the source data producers?

The dataset was created by annotators who are trained in RPA tool usage, multilingual content creation, and data anonymization.

Annotations

Annotation process

Tooling: Custom-built annotation platform with Playwright integration.
Granularity: Each interaction, browser command, and user feedback request was recorded as an individual annotation step.
Metadata: Each action is linked to the intent, language, and required parameters.
Itineraries: Canonical action sequences defined per intent to ensure coverage and consistency.
Review: All annotations were anonymized automatically; a sample was manually checked for compliance.

Personal and Sensitive Information

The dataset contains no real personal data.
During annotation, realistic values (e.g., NIF, IBAN, license plates) were required to progress in real systems, but:

Real values remained local to the annotator’s machine.
An anonymization configuration file (config_anonymizer.csv) mapped real values to synthetic placeholders.
The public dataset only includes anonymized values stored in anonymized_data.json.

Recommendations

Before deploying models trained on this dataset in production, validate them in controlled environments.
Although the dataset is domain-accurate; for production, complement with real in-domain RPA logs.
Especially in high-stakes contexts (e.g., government filings, financial operations), always keep a human in the loop.
Each language variant is unique, so models should be tested per language to avoid performance gaps.

Glossary [optional]

Intent: High-level description of the task (e.g., “consult vehicle tax data”).
Itinerary: Ordered sequence of RPA steps to complete a specific request.
Browser action: Automation step executed directly without user input (e.g., click, navigate).
User feedback: Step requiring user input before continuing (e.g., entering SMS code).
Quadruple: Four-part action annotation (JSON code, description, screenshot, HTML).
Anonymized data: Synthetic replacements for sensitive personal information.

More Information

This work/research has been promoted and financed by the Government of Catalonia through the Aina project.

Dataset Card Contact

Language Technologies Laboratory (langtech@bsc.es) at the Barcelona Supercomputing Center (BSC).

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