Triple

T16013088
Position Surface form Disambiguated ID Type / Status
Subject Violante Beatrix of Bavaria E388389 entity
Predicate residence P75 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: [Violante Beatrix of Bavaria, residence, Siena]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Siena
Context triple: [Violante Beatrix of Bavaria, residence, 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_69d86dabcb7c8190b6a39d6831d2fa1b completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e18291e2b481909d13cb6057c76cee completed April 17, 2026, 12:45 a.m.
NED1 Entity disambiguation (via context triple) batch_69ffdbcc12dc8190a80d776b63a6ad35 completed May 10, 2026, 1:13 a.m.
Created at: April 10, 2026, 4:55 a.m.