Triple

T17821617
Position Surface form Disambiguated ID Type / Status
Subject Charlotte of Savoy E444998 entity
Predicate deathPlace P21 FINISHED
Object Amboise NE NERFINISHED

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: Amboise | Statement: [Charlotte of Savoy, deathPlace, Amboise]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Amboise
Context triple: [Charlotte of Savoy, deathPlace, Amboise]
  • A. Amboise chosen
    Amboise is a historic town in central France on the Loire River, known for its royal château and as the place where Leonardo da Vinci spent his final years.
  • B. Blois
    Blois is a historic city in central France known for its Renaissance château, picturesque setting on the Loire River, and rich royal heritage.
  • C. Beaugency
    Beaugency is a historic town in north-central France on the Loire River, known for its medieval architecture and strategic role in the Hundred Years' War.
  • D. Châteaudun
    Châteaudun is a historic town in north-central France known for its medieval château overlooking the Loir River and its role as a gateway to the Loire Valley.
  • E. Chinon
    Chinon is a renowned Loire Valley wine appellation in France, best known for its elegant, medium-bodied red wines primarily made from Cabernet Franc.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8b9f0de78819099395b14db75a8a6 completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e48911b660819097fc7ea94665a02a completed April 19, 2026, 7:49 a.m.
Created at: April 10, 2026, 10:15 a.m.