Triple

T12251676
Position Surface form Disambiguated ID Type / Status
Subject Grolleau E291985 entity
Predicate primaryRegion P1103 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: [Grolleau, primaryRegion, Anjou]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Anjou
Context triple: [Grolleau, primaryRegion, 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. Anjou AOC
    Anjou AOC is a French wine appellation in the Loire Valley known for producing a wide range of red, white, and rosé wines, including the famous Rosé d’Anjou.
  • D. Marmande
    Marmande is a town in southwestern France known for its agricultural production, particularly tomatoes, and its location in the Garonne River valley.
  • E. Auberjonois
    Auberjonois is a surname most prominently associated with René Auberjonois, an American actor known for roles in film, television, and voice work.
  • 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_69d6ab67950c8190be08450a06228c4b completed April 8, 2026, 7:24 p.m.
NER Named-entity recognition batch_69d91cc6983c81909bf479d15879a357 completed April 10, 2026, 3:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69f60aa13f64819096dc23295a6f0cdb completed May 2, 2026, 2:30 p.m.
Created at: April 8, 2026, 9:52 p.m.