Triple

T5967736
Position Surface form Disambiguated ID Type / Status
Subject Louis XVII of France E132794 entity
Predicate birthPlace P1 FINISHED
Object Versailles, France E9321 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: Versailles, France | Statement: [Louis XVII of France, birthPlace, Versailles, France]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Versailles, France
Context triple: [Louis XVII of France, birthPlace, Versailles, France]
  • A. Versailles
    Versailles is a small borough in Allegheny County, Pennsylvania, situated along the Youghiogheny River in the Pittsburgh metropolitan area.
  • B. Versailles chosen
    Versailles is a historic French city best known for the opulent Palace of Versailles, a former royal residence and a symbol of absolute monarchy and French cultural grandeur.
  • C. Blois, France
    Blois, France is a historic city on the Loire River known for its Renaissance château and as the birthplace of King Stephen of England.
  • D. Fontainebleau, France
    Fontainebleau, France is a historic town southeast of Paris best known for its vast forest and royal château, long associated with French monarchs and outdoor recreation.
  • E. Rambouillet, France
    Rambouillet, France is a historic town southwest of Paris known for its royal château, former role as a French royal and presidential residence, and surrounding forest.
  • 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_69c0086deab081908550159ca23eec9b completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c03a3f612481908744cb645f2ede1d completed March 22, 2026, 6:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0e3ff62f08190be56bb9c450c9647 completed March 23, 2026, 6:55 a.m.
Created at: March 22, 2026, 4:03 p.m.