Triple

T26449724
Position Surface form Disambiguated ID Type / Status
Subject Creuse River E665311 entity
Predicate mouthOfWaterBody P3817 FINISHED
Object Vienne River
The Vienne River is a major river in west-central France that flows through the Limousin and Poitou regions before joining the Loire.
 E252485 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: Vienne River | Statement: [Creuse River, mouthOfWaterBody, Vienne River]
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Vienne River
Triple: [Creuse River, mouthOfWaterBody, Vienne River]
Generated description
The Vienne River is a major river in west-central France that flows through the Limousin and Poitou regions before joining the Loire.

Provenance (5 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_69ee883d5040819097dd154643005230 completed April 26, 2026, 9:48 p.m.
NER Named-entity recognition batch_69f612641a10819083c65b529fdade2a completed May 2, 2026, 3:04 p.m.
NED1 Entity disambiguation (via context triple) batch_6a13031ebafc8190857a791540e243d3 completed May 24, 2026, 1:54 p.m.
NEDg Description generation batch_6a13047e2c708190a575e3b0c1930c2f completed May 24, 2026, 2 p.m.
NED2 Entity disambiguation (via description) batch_6a1304efd82481909d557a7c07c29c9f completed May 24, 2026, 2:02 p.m.
Created at: April 27, 2026, 12:04 a.m.