Triple

T2471063
Position Surface form Disambiguated ID Type / Status
Subject Peter Townsend E55372 entity
Predicate placeOfDeath P21 FINISHED
Object Rambouillet E132848 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: Rambouillet | Statement: [Peter Townsend, placeOfDeath, Rambouillet]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rambouillet
Context triple: [Peter Townsend, placeOfDeath, Rambouillet]
  • A. Rambouillet, France chosen
    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.
  • B. Thoiry
    Thoiry is a commune in the Ain department of eastern France, located near the Swiss border in the Pays de Gex region.
  • C. Compiegne
    Compiègne is a historic city in northern France known for its royal château, forest, and role in significant events such as the signing of the 1918 Armistice.
  • D. Rocquencourt
    Rocquencourt is a commune in north-central France that historically hosted key NATO military command facilities.
  • E. Vichy
    Vichy is a spa town in central France renowned for its thermal springs, health resorts, and role as the seat of the World War II Vichy regime.
  • 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_69ab49e3622c8190ad22afa2c4fbb807 completed March 6, 2026, 9:40 p.m.
NER Named-entity recognition batch_69abd136f5388190801d0b9dc66ad36f completed March 7, 2026, 7:18 a.m.
NED1 Entity disambiguation (via context triple) batch_69af1f86a1bc8190af02a1109ccf0773 completed March 9, 2026, 7:29 p.m.
Created at: March 6, 2026, 9:44 p.m.