Triple

T28177013
Position Surface form Disambiguated ID Type / Status
Subject Roquebrune-Cap-Martin railway station E715918 entity
Predicate adjacentStation P5707 FINISHED
Object Carnolès railway station
Carnolès railway station is a local train stop on the coastal rail line in the commune of Roquebrune-Cap-Martin in southeastern France, serving regional passenger traffic along the French Riviera.
E1805367 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: Carnolès railway station | Statement: [Roquebrune-Cap-Martin railway station, adjacentStation, Carnolès 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: Carnolès railway station
Triple: [Roquebrune-Cap-Martin railway station, adjacentStation, Carnolès railway station]
Generated description
Carnolès railway station is a local train stop on the coastal rail line in the commune of Roquebrune-Cap-Martin in southeastern France, serving regional passenger traffic along the French Riviera.

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_69efd6b4fc5c81909dd88f01a8c2b35d completed April 27, 2026, 9:35 p.m.
NER Named-entity recognition batch_69f6423b561c819088edf7b1cd739d75 completed May 2, 2026, 6:28 p.m.
NED1 Entity disambiguation (via context triple) batch_6a15d7c1bf108190b28a8f819dab05b1 completed May 26, 2026, 5:26 p.m.
NEDg Description generation batch_6a15d9fbb47081909109f6ed533bc8ac completed May 26, 2026, 5:35 p.m.
NED2 Entity disambiguation (via description) batch_6a15daaf33588190b5aa74d272349389 completed May 26, 2026, 5:38 p.m.
Created at: April 27, 2026, 10:17 p.m.