Triple

T22296509
Position Surface form Disambiguated ID Type / Status
Subject Havre Mountains E551134 entity
Predicate namedAfter P63 FINISHED
Object Havre 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: Havre | Statement: [Havre Mountains, namedAfter, Havre]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Havre
Context triple: [Havre Mountains, namedAfter, Havre]
  • A. Havre-Saint-Pierre
    Havre-Saint-Pierre is a small coastal town on the north shore of the Gulf of Saint Lawrence in Quebec, Canada, known as a gateway to the Mingan Archipelago National Park Reserve.
  • B. Cherbourg
    Cherbourg is a rural Aboriginal community in southern Queensland, Australia, known for its significant Indigenous history and culture.
  • C. Cherbourg
    Cherbourg is a major French port city on the Cotentin Peninsula, known for its strategic naval harbor and cross-Channel ferry connections.
  • D. Saint-Nazaire
    Saint-Nazaire is a major Atlantic port city in western France, known for its shipbuilding industry and strategic location at the mouth of the Loire River.
  • E. Port of Le Havre chosen
    The Port of Le Havre is one of France’s largest and busiest seaports, serving as a major gateway for maritime trade on the English Channel and the North Sea.
  • 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_69e11e45fb848190a1b2ae21296e3a5f completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f15720fba0819080f6c96f6df4f1e0 completed April 29, 2026, 12:56 a.m.
Created at: April 16, 2026, 8:41 p.m.