Triple

T9316226
Position Surface form Disambiguated ID Type / Status
Subject Normandy (administrative region) E224127 entity
Predicate contains P35 FINISHED
Object Alençon E348749 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: Alençon | Statement: [Normandy (administrative region), contains, Alençon]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Alençon
Context triple: [Normandy (administrative region), contains, Alençon]
  • A. Alençon chosen
    Alençon is a historic town in northwestern France renowned for its fine lace-making tradition and architectural heritage.
  • B. Chapeauroux
    Chapeauroux is a river in central France that flows through the Massif Central before joining the Allier.
  • C. Evreux
    Evreux is a historic town in northern France, known for its Gothic cathedral and role as the capital of the Eure department in Normandy.
  • D. Doué-en-Anjou
    Doué-en-Anjou is a commune in western France known for its troglodyte dwellings and wine production in the Maine-et-Loire department of the Pays de la Loire region.
  • E. Angers
    Angers is a historic city in western France known for its medieval architecture, including the Château d'Angers and its famous Apocalypse Tapestry.
  • 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_69ca8425f4fc81909c1c586e9a5b7530 completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd358846e48190a8aacfab19d88ae7 completed April 1, 2026, 3:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69d1cc3114ec8190ba80c9059481f946 completed April 5, 2026, 2:42 a.m.
Created at: March 30, 2026, 7:37 p.m.