Triple

T9171794
Position Surface form Disambiguated ID Type / Status
Subject Province of Lucca E220097 entity
Predicate contains P35 FINISHED
Object City of Lucca E364247 NE FINISHED

How this triple was built (2 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: City of Lucca | Statement: [Province of Lucca, contains, City of Lucca]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: City of Lucca
Context triple: [Province of Lucca, contains, City of Lucca]
  • A. city of Lucca chosen
    The city of Lucca is a historic Tuscan city in central Italy, renowned for its well-preserved Renaissance walls, medieval architecture, and rich cultural heritage.
  • B. San Gimignano
    San Gimignano is a medieval hill town in Tuscany, Italy, renowned for its well-preserved tower houses and historic cityscape.
  • C. Faenza
    Faenza is a historic city in Italy’s Emilia-Romagna region, renowned for its traditional ceramics and artistic majolica production.
  • D. Pesaro
    Pesaro is a coastal city on Italy’s Adriatic Sea, known for its Renaissance architecture, seaside resorts, and as the birthplace of composer Gioachino Rossini.
  • E. Arezzo
    Arezzo is an ancient Tuscan city in central Italy, historically significant as one of the principal centers of the Etruscan civilization and later a prominent medieval and Renaissance town.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69ca83e467108190abcae6a33b3d4dad completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69ccaae38ee48190bf783477bc37913d completed April 1, 2026, 5:19 a.m.
NED1 Entity disambiguation (via context triple) batch_69d065cd42f481909ad3c68372041b1a completed April 4, 2026, 1:13 a.m.
Created at: March 30, 2026, 7:22 p.m.