Triple

T10311222
Position Surface form Disambiguated ID Type / Status
Subject Transilien Line R E241893 entity
Predicate servesDepartment P1204 FINISHED
Object Loiret E210466 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: Loiret | Statement: [Transilien Line R, servesDepartment, Loiret]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Loiret
Context triple: [Transilien Line R, servesDepartment, Loiret]
  • A. Loiret chosen
    Loiret is a department in north-central France, named after the Loiret River and known for its historic towns and proximity to the Loire Valley.
  • B. Yonne
    Yonne is a major river in north-central France that flows through the Burgundy region before joining the Seine.
  • C. Loir
    The Loir is a river in central France that flows through the regions of Pays de la Loire and Centre-Val de Loire before joining the Sarthe.
  • D. Loire
    The Loire is the longest river in France, renowned for its scenic valley dotted with historic châteaux and vineyards.
  • E. Loire
    Loire is a department in central-eastern France named after the Loire River, known for its varied landscapes, industrial cities like Saint-Étienne, and historical ties to the broader Loire Valley region.
  • 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_69d381ac38808190a8ca7457c85b625b completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4d32ac6c08190b23eb042b3ec284a completed April 7, 2026, 9:49 a.m.
NED1 Entity disambiguation (via context triple) batch_69ef8185c6e08190949020a80c24f2b8 completed April 27, 2026, 3:32 p.m.
Created at: April 6, 2026, 11:47 a.m.