Triple

T23655479
Position Surface form Disambiguated ID Type / Status
Subject Basse-Allaine E584286 entity
Predicate hasRailwayStation P918 FINISHED
Object Courtemaîche railway station
Courtemaîche railway station is a local Swiss railway stop serving the village of Courtemaîche in the municipality of Basse-Allaine in the canton of Jura.
E1599739 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: Courtemaîche railway station | Statement: [Basse-Allaine, hasRailwayStation, Courtemaîche railway station]
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: Courtemaîche railway station
Triple: [Basse-Allaine, hasRailwayStation, Courtemaîche railway station]
Generated description
Courtemaîche railway station is a local Swiss railway stop serving the village of Courtemaîche in the municipality of Basse-Allaine in the canton of Jura.

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_69e248ffc0888190ae23c4731eb8b7ac completed April 17, 2026, 2:51 p.m.
NER Named-entity recognition batch_69f1b35b19e48190866a19ed8b7086d0 completed April 29, 2026, 7:29 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0f53a1a34481909919688f9222f9eb completed May 21, 2026, 6:49 p.m.
NEDg Description generation batch_6a0f54af0b108190a7c3e0ac0f48aabf completed May 21, 2026, 6:53 p.m.
NED2 Entity disambiguation (via description) batch_6a0f5587b89481908744d12128349956 completed May 21, 2026, 6:57 p.m.
Created at: April 17, 2026, 6:49 p.m.