Triple

T19221436
Position Surface form Disambiguated ID Type / Status
Subject Saint-Pourçain-sur-Sioule E480623 entity
Predicate locatedOn P40 FINISHED
Object Sioule River
The Sioule River is a tributary of the Allier in central France, known for flowing through the Auvergne region’s rural landscapes and gorges.
E1740151 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: Sioule River | Statement: [Saint-Pourçain-sur-Sioule, locatedOn, Sioule 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: Sioule River
Triple: [Saint-Pourçain-sur-Sioule, locatedOn, Sioule River]
Generated description
The Sioule River is a tributary of the Allier in central France, known for flowing through the Auvergne region’s rural landscapes and gorges.

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_69d8e8cb8c348190b52075823911c869 completed April 10, 2026, 12:10 p.m.
NER Named-entity recognition batch_69e5fa3fa9348190920f9d41b8beb900 completed April 20, 2026, 10:04 a.m.
NED1 Entity disambiguation (via context triple) batch_6a1209097a1c81908674095e7a052489 completed May 23, 2026, 8:07 p.m.
NEDg Description generation batch_6a120a10905c819096fa77fad68b6bb8 completed May 23, 2026, 8:12 p.m.
NED2 Entity disambiguation (via description) batch_6a120aeed5ec819097f7ac08533bcf65 completed May 23, 2026, 8:15 p.m.
Created at: April 10, 2026, 1:24 p.m.