Triple

T3531768
Position Surface form Disambiguated ID Type / Status
Subject Southern France E74674 entity
Predicate hasRiver P165 FINISHED
Object Dordogne E78217 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: Dordogne | Statement: [Southern France, hasRiver, Dordogne]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dordogne
Context triple: [Southern France, hasRiver, Dordogne]
  • A. Dordogne chosen
    Dordogne is a major river in southwestern France known for flowing through the Dordogne valley, a region famed for its picturesque landscapes, historic towns, and prehistoric cave art.
  • B. Aveyron
    Aveyron is a rural department in southern France known for its rugged landscapes, medieval villages, and traditional gastronomy including Roquefort cheese.
  • C. Gironde
    Gironde is a department in southwestern France that encompasses much of the Bordeaux wine region, including renowned appellations such as Graves.
  • D. Rouergue
    Rouergue is a historic cultural region in southern France, centered around the present-day Aveyron department and known for its rural landscapes, medieval towns, and Occitan heritage.
  • E. Touraine
    Touraine is a historic region in central France, famed for its Loire Valley châteaux, wine production, and role as a former royal heartland.
  • 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_69ad85d1a3948190931fd1ea1f49717b completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adbc9a14c881908932b17ed3eececb completed March 8, 2026, 6:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69b38bcc879c8190ab4ab3e2b67d9a16 completed March 13, 2026, 4 a.m.
Created at: March 8, 2026, 3:19 p.m.