Triple

T6178846
Position Surface form Disambiguated ID Type / Status
Subject Garden of France E137886 entity
Predicate includesCity P3207 FINISHED
Object Amboise E135329 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: Amboise | Statement: [Garden of France, includesCity, Amboise]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Amboise
Context triple: [Garden of France, includesCity, 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. 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.
  • D. 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.
  • E. Bourges
    Bourges is a historic city in central France known for its well-preserved medieval architecture and its UNESCO-listed Gothic cathedral, Saint-Étienne.
  • 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_69c008a80f748190ba3d07ffc81acb29 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c05dcb77948190b5385438f81bf0a8 completed March 22, 2026, 9:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69c141bf3f4081909849e38d322da251 completed March 23, 2026, 1:35 p.m.
Created at: March 22, 2026, 4:18 p.m.