Triple

T25762776
Position Surface form Disambiguated ID Type / Status
Subject Tour de la Massane E648787 entity
Predicate namedAfter P63 FINISHED
Object Massane (local toponym)
Massane is a local place name in southern France, likely referring to a nearby stream or geographic feature that gives its name to landmarks such as the Tour de la Massane.
E1693597 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: Massane (local toponym) | Statement: [Tour de la Massane, namedAfter, Massane (local toponym)]
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: Massane (local toponym)
Triple: [Tour de la Massane, namedAfter, Massane (local toponym)]
Generated description
Massane is a local place name in southern France, likely referring to a nearby stream or geographic feature that gives its name to landmarks such as the Tour de la Massane.

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_69e7ab322db0819092d6a2b3d4572e01 completed April 21, 2026, 4:52 p.m.
NER Named-entity recognition batch_69f5fdf12528819093c47b3af6b865ef completed May 2, 2026, 1:36 p.m.
NED1 Entity disambiguation (via context triple) batch_6a10cc18d4108190806ec23892188faa completed May 22, 2026, 9:35 p.m.
NEDg Description generation batch_6a10cc9f320c8190b958be1f0075cd8f completed May 22, 2026, 9:37 p.m.
NED2 Entity disambiguation (via description) batch_6a10cdf9537481909131c59b126e69b6 completed May 22, 2026, 9:43 p.m.
Created at: April 22, 2026, 5:07 a.m.