Triple

T4822023
Position Surface form Disambiguated ID Type / Status
Subject Pope Alexander III E107731 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: [Pope Alexander III, birthPlace, Siena]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Siena
Context triple: [Pope Alexander III, 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. 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_69bd43f9efa081908314cb3e94fa1695 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd6caa95ec8190bea525dbf3a00477 completed March 20, 2026, 3:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69be89d3358c8190bb85ec1835a9f095 completed March 21, 2026, 12:06 p.m.
Created at: March 20, 2026, 1:24 p.m.