Triple

T1868258
Position Surface form Disambiguated ID Type / Status
Subject John E34971 entity
Predicate lostTerritory P356 FINISHED
Object Anjou E24104 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: Anjou | Statement: [John, lostTerritory, Anjou]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Anjou
Context triple: [John, lostTerritory, Anjou]
  • A. Anjou chosen
    Anjou is a historic region in western France that was once a powerful medieval county and later a duchy, playing a central role in the Angevin Empire and European dynastic politics.
  • B. Anjou
    Anjou is a residential borough in the eastern part of Montreal, Quebec, known for its suburban character and shopping centers.
  • C. Marmande
    Marmande is a town in southwestern France known for its agricultural production, particularly tomatoes, and its location in the Garonne River valley.
  • D. Saintonge
    Saintonge is a historic coastal region in western France, centered around the town of Saintes and known for its Romanesque heritage and early production of cognac.
  • E. Confignon
    Confignon is a small municipality in the canton of Geneva in southwestern Switzerland, known for its residential character and proximity to the city of Geneva.
  • 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_69a88600b2f88190bc09303e68ab517e completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69abb0b6ac108190921c197abc5ab5b5 completed March 7, 2026, 4:59 a.m.
NED1 Entity disambiguation (via context triple) batch_69add1d8dd8881909189029a047bc2b4 completed March 8, 2026, 7:45 p.m.
Created at: March 4, 2026, 7:34 p.m.