Triple

T4879343
Position Surface form Disambiguated ID Type / Status
Subject Gothic art E109284 entity
Predicate notableCenter P16715 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: [Gothic art, notableCenter, Siena]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Siena
Context triple: [Gothic art, notableCenter, 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. San Gimignano
    San Gimignano is a medieval hill town in Tuscany, Italy, renowned for its well-preserved tower houses and historic cityscape.
  • C. Pistoia
    Pistoia is a historic Italian city known for its medieval architecture, vibrant cultural heritage, and location in the northern part of Tuscany.
  • D. 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.
  • E. Prato
    Prato is a historic Tuscan city in central Italy known for its textile industry, medieval architecture, and cultural heritage.
  • 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_69bd440e9d64819083e82cf33b4d9570 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd6dbf37ac819085bb758bc6406271 completed March 20, 2026, 3:54 p.m.
NED1 Entity disambiguation (via context triple) batch_69be9235e7b8819084fd9eb7c794e0e3 completed March 21, 2026, 12:42 p.m.
Created at: March 20, 2026, 1:27 p.m.