Triple

T9749189
Position Surface form Disambiguated ID Type / Status
Subject Indre E236394 entity
Predicate hasRiver P165 FINISHED
Object Creuse River E665311 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: Creuse River | Statement: [Indre, hasRiver, Creuse River]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Creuse River
Context triple: [Indre, hasRiver, Creuse River]
  • A. Creuse River chosen
    The Creuse River is a major river in central France that flows through the historical regions of Berry and Limousin, known for its scenic valleys and picturesque landscapes.
  • B. Charentonne River
    The Charentonne River is a watercourse in northern France that flows through the town of Bernay and contributes to the region’s rural and historical landscape.
  • C. Creuse
    Creuse is a rural department in central France known for its sparsely populated landscapes, traditional agriculture, and part of the historic Limousin region.
  • D. Sée River
    The Sée River is a coastal river in northwestern France that flows through Normandy before emptying into the Bay of Mont-Saint-Michel.
  • E. Aveyron River
    The Aveyron River is a waterway in southern France known for flowing through scenic gorges and historic towns before joining the Tarn River.
  • 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_69ca84d4eddc8190996fec1417d2bae8 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cd9f6a2f8c8190a6f6af6587ee90b8 completed April 1, 2026, 10:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69e3e686db808190a2aa975a20e69696 completed April 18, 2026, 8:16 p.m.
Created at: March 30, 2026, 8:23 p.m.