Triple

T20786452
Position Surface form Disambiguated ID Type / Status
Subject FR-61 E511650 entity
Predicate subdivisionName P747 FINISHED
Object Orne NE NERFINISHED

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: Orne | Statement: [FR-61, subdivisionName, Orne]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Orne
Context triple: [FR-61, subdivisionName, Orne]
  • A. Orne chosen
    Orne is a rural department in northwestern France known for its pastoral landscapes, horse breeding, and historic towns such as Alençon.
  • B. Orne Saosnoise
    Orne Saosnoise is a smaller river in northwestern France that serves as a tributary of the Orne River.
  • C. Olne
    Olne is a small municipality in the province of Liège in Wallonia, eastern Belgium, known for its rural character and traditional village charm.
  • D. The Nore
    The Nore is a sandbank at the mouth of the Thames Estuary in England that historically served as a major Royal Navy anchorage and site of naval command.
  • E. Nerstrand
    Nerstrand is a small city in southeastern Minnesota known for its proximity to Nerstrand-Big Woods State Park and its rural, community-oriented character.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b4cb83948190bd57bec21d78ed53 completed April 16, 2026, 10:07 a.m.
NER Named-entity recognition batch_69e6c28c0d0c8190aa48e6fdfdaab750 completed April 21, 2026, 12:19 a.m.
Created at: April 16, 2026, 12:38 p.m.