Triple

T24323758
Position Surface form Disambiguated ID Type / Status
Subject Marais Poitevin Regional Natural Park E613039 entity
Predicate traversedBy P225 FINISHED
Object Lay River
The Lay River is a watercourse in western France that flows through the Vendée department and contributes to the wetland landscapes of the Marais Poitevin region.
E2291174 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: Lay River | Statement: [Marais Poitevin Regional Natural Park, traversedBy, Lay 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: Lay River
Triple: [Marais Poitevin Regional Natural Park, traversedBy, Lay River]
Generated description
The Lay River is a watercourse in western France that flows through the Vendée department and contributes to the wetland landscapes of the Marais Poitevin region.

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_69e2d7db6d5c819091194918157a7c1f completed April 18, 2026, 1:01 a.m.
NER Named-entity recognition batch_69f292ae127881909ef1772278181ce3 completed April 29, 2026, 11:22 p.m.
NED1 Entity disambiguation (via context triple) batch_6a5c340a152881908cd4bf7eca717543 completed July 19, 2026, 2:18 a.m.
NEDg Description generation batch_6a5c355231c4819083c512f7ceb7538f completed July 19, 2026, 2:24 a.m.
NED2 Entity disambiguation (via description) batch_6a5c35c51e9c819085aca491cf377e71 completed July 19, 2026, 2:26 a.m.
Created at: April 18, 2026, 1:53 a.m.