Triple

T8837130
Position Surface form Disambiguated ID Type / Status
Subject La Marche E210292 entity
Predicate partlyCorrespondsToModernDepartment P84931 FINISHED
Object Indre E241347 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: Indre | Statement: [La Marche, partlyCorrespondsToModernDepartment, Indre]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Indre
Context triple: [La Marche, partlyCorrespondsToModernDepartment, Indre]
  • A. Indre chosen
    Indre is a rural department in central France known for its quiet countryside, historic towns, and location within the Centre-Val de Loire region.
  • B. Indre
    Indre is a river in central France that flows through the regions of Berry and Touraine before joining the Loire.
  • C. Endre
    Endre is the Hungarian given name of film director André De Toth, known for his work in mid-20th-century cinema.
  • D. Innlandet
    Innlandet is a county in eastern Norway known for its inland landscapes, including mountains, forests, and important winter sports venues.
  • E. Innlandet
    Innlandet is an island district of the Norwegian town of Kristiansund, known for its traditional wooden houses and coastal maritime character.
  • 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_69ca8388549c819095fd94eadefbb007 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc606adde08190825dbdabd199c025 completed April 1, 2026, 12:01 a.m.
NED1 Entity disambiguation (via context triple) batch_69cf898a478c81908f138a78f331b87d completed April 3, 2026, 9:34 a.m.
Created at: March 30, 2026, 6:48 p.m.