Triple

T16667802
Position Surface form Disambiguated ID Type / Status
Subject Francesco Todeschini Piccolomini E405028 entity
Predicate birthPlace P1 FINISHED
Object Siena E168770 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: Siena | Statement: [Francesco Todeschini Piccolomini, birthPlace, Siena]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Siena
Context triple: [Francesco Todeschini Piccolomini, birthPlace, Siena]
  • A. Siena chosen
    Siena is a historic Tuscan city renowned for its medieval brick architecture, fan-shaped Piazza del Campo, and the Palio horse race.
  • B. SIENA
    SIENA is a secure communication platform used primarily by European law enforcement agencies to exchange sensitive information and coordinate cross-border operations.
  • C. San Gimignano
    San Gimignano is a medieval hill town in Tuscany, Italy, renowned for its well-preserved tower houses and historic cityscape.
  • D. Pistoia
    Pistoia is a historic Italian city known for its medieval architecture, vibrant cultural heritage, and location in the northern part of Tuscany.
  • E. San Miniato
    San Miniato is a historic hilltop town in Tuscany, Italy, known for its medieval architecture and prized white truffles.
  • 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_69d8838b5fbc81908c6575c132b82e80 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e37c9e9a208190afab499897ce4361 completed April 18, 2026, 12:44 p.m.
NED1 Entity disambiguation (via context triple) batch_6a008a34852c81908c00ff8e36923cee completed May 10, 2026, 1:37 p.m.
Created at: April 10, 2026, 5:18 a.m.