Triple

T16762233
Position Surface form Disambiguated ID Type / Status
Subject Normandy waterways network E407373 entity
Predicate traverses P416 FINISHED
Object Orne E123324 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: Orne | Statement: [Normandy waterways network, traverses, Orne]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Orne
Context triple: [Normandy waterways network, traverses, 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. Olne
    Olne is a small municipality in the province of Liège in Wallonia, eastern Belgium, known for its rural character and traditional village charm.
  • C. 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.
  • D. Norane
    Norane is a small settlement or locality within the municipality of Sogndal in Vestland county, western Norway.
  • E. Møse
    Møse is a Norwegian surname most notably borne by Erik Møse, a prominent jurist and international judge.
  • 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_69d8839174188190909f190097207065 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e3abed67f88190afb1d392ff01a5e7 completed April 18, 2026, 4:06 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00a52d077081908080c61da67e0032 completed May 10, 2026, 3:33 p.m.
Created at: April 10, 2026, 5:21 a.m.