Triple

T19405707
Position Surface form Disambiguated ID Type / Status
Subject Crowdy Head E485453 entity
Predicate hasNearbySettlement P4647 FINISHED
Object Harrington 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: Harrington | Statement: [Crowdy Head, hasNearbySettlement, Harrington]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Harrington
Context triple: [Crowdy Head, hasNearbySettlement, Harrington]
  • A. Harrington chosen
    Harrington is a small coastal town in New South Wales, Australia, known for its beaches, fishing, and proximity to the Manning River and Crowdy Bay National Park.
  • B. Harrington
    Harrington is a surname of English and Irish origin borne by numerous notable individuals across fields such as politics, science, and the arts.
  • C. Hannan
    Hannan is a coastal city in southern Osaka Prefecture, Japan, known for its fishing industry and proximity to Osaka Bay.
  • D. Hannington
    Hannington is a small rural village in the English county of Hampshire, known for its traditional countryside setting and historic character.
  • E. Hannington
    Hannington is a small rural village in Wiltshire, England, known for its traditional English countryside setting and historic 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_69d8e8d5162481909db12435d9535c1a completed April 10, 2026, 12:11 p.m.
NER Named-entity recognition batch_69e6257af68881908147beedc29ff64c completed April 20, 2026, 1:09 p.m.
Created at: April 10, 2026, 1:36 p.m.