Triple

T10913795
Position Surface form Disambiguated ID Type / Status
Subject Transilien Line U E257767 entity
Predicate terminusStation P15150 FINISHED
Object La Verrière E601933 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: La Verrière | Statement: [Transilien Line U, terminusStation, La Verrière]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: La Verrière
Context triple: [Transilien Line U, terminusStation, La Verrière]
  • A. La Verrière chosen
    La Verrière is a suburban commune in the Yvelines department of north-central France, located within the Paris metropolitan area.
  • B. Vauvert
    Vauvert is a commune in southern France known for its location in the Gard department near the Camargue region.
  • C. Mouriès
    Mouriès is a village in southern France’s Provence region, known for its olive oil production and location near the Alpilles hills.
  • D. Éveux
    Éveux is a small commune in eastern France’s Rhône department, known for hosting Le Corbusier’s modernist monastery, the Couvent Sainte-Marie de La Tourette.
  • E. Saussignac
    Saussignac is a small wine-producing commune in southwestern France, known for its sweet white wines made primarily from Sémillon and other Bordeaux grape varieties.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69d6aa864ed88190818280ab6791d065 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d77073d12881908ea59771b84bc804 completed April 9, 2026, 9:25 a.m.
NED1 Entity disambiguation (via context triple) batch_69e34455ea4c8190b6f2433f3f745b76 completed April 18, 2026, 8:44 a.m.
Created at: April 8, 2026, 9:22 p.m.