Triple

T3568088
Position Surface form Disambiguated ID Type / Status
Subject Angela Maria Pietrasanta E75499 entity
Predicate familyName P18 FINISHED
Object Pietrasanta
Pietrasanta is an Italian surname of likely toponymic origin, associated with individuals such as Angela Maria Pietrasanta.
E425451 NE FINISHED

How this triple was built (4 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Pietrasanta | Statement: [Angela Maria Pietrasanta, familyName, Pietrasanta]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pietrasanta
Context triple: [Angela Maria Pietrasanta, familyName, Pietrasanta]
  • A. Denia
    Denia is a coastal city on Spain’s Costa Blanca known for its historic castle, Mediterranean beaches, and vibrant port.
  • B. Pontevedra
    Pontevedra is a coastal municipality in the province of Capiz in the Philippines, known for its fishing communities and agricultural economy.
  • C. Pontevedra
    Pontevedra is a coastal province in northwestern Spain known for its historic towns, Atlantic landscapes, and location within the autonomous community of Galicia.
  • D. Quarteira
    Quarteira is a coastal town in Portugal’s Algarve region known for its long sandy beaches, seaside promenade, and role as a popular holiday resort.
  • E. Gandia
    Gandia is a coastal city in eastern Spain known for its Mediterranean beaches, historical heritage, and role as a tourist destination in the province of Valencia.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Pietrasanta
Triple: [Angela Maria Pietrasanta, familyName, Pietrasanta]
Generated description
Pietrasanta is an Italian surname of likely toponymic origin, associated with individuals such as Angela Maria Pietrasanta.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Pietrasanta
Target entity description: Pietrasanta is an Italian surname of likely toponymic origin, associated with individuals such as Angela Maria Pietrasanta.
  • A. Denia
    Denia is a coastal city on Spain’s Costa Blanca known for its historic castle, Mediterranean beaches, and vibrant port.
  • B. Pontevedra
    Pontevedra is a coastal municipality in the province of Capiz in the Philippines, known for its fishing communities and agricultural economy.
  • C. Pontevedra
    Pontevedra is a coastal province in northwestern Spain known for its historic towns, Atlantic landscapes, and location within the autonomous community of Galicia.
  • D. Quarteira
    Quarteira is a coastal town in Portugal’s Algarve region known for its long sandy beaches, seaside promenade, and role as a popular holiday resort.
  • E. Gandia
    Gandia is a coastal city in eastern Spain known for its Mediterranean beaches, historical heritage, and role as a tourist destination in the province of Valencia.
  • F. None of above. chosen

Provenance (5 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69ad85d512708190829c8b2d3a2ccfb8 completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc0ab51d881908f004fae47ab09d9 completed March 8, 2026, 6:32 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5b73c409081909c583019d7ec1d4a completed March 14, 2026, 7:30 p.m.
NEDg Description generation batch_69b5b7e7f48881908ebb773499aebd5e completed March 14, 2026, 7:32 p.m.
NED2 Entity disambiguation (via description) batch_69b5b881c80081909af084ff4b43b01e completed March 14, 2026, 7:35 p.m.
Created at: March 8, 2026, 3:21 p.m.