Triple

T11715144
Position Surface form Disambiguated ID Type / Status
Subject Kensington, New South Wales E278476 entity
Predicate adjacentSuburb P37779 FINISHED
Object Daceyville E867483 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: Daceyville | Statement: [Kensington, New South Wales, adjacentSuburb, Daceyville]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Daceyville
Context triple: [Kensington, New South Wales, adjacentSuburb, Daceyville]
  • A. Daceyville chosen
    Daceyville is a small residential suburb in Sydney, Australia, known as one of the country’s earliest public housing garden suburbs.
  • B. Wallaceville
    Wallaceville is a residential suburb located within the Hutt Valley region near Wellington, New Zealand.
  • C. Snowville
    Snowville is a small rural settlement located within the township of Tehkummah in Ontario, Canada.
  • D. Tierceville
    Tierceville is a small commune in the Calvados department of the Normandy region in northwestern France.
  • E. Lantzville
    Lantzville is a small coastal community and district municipality on central Vancouver Island in British Columbia, Canada, known for its residential character and seaside setting.
  • 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_69d6aaff2ce88190b4a1e4b341ad5377 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8a4bf54d88190a8e07fbbf8d9e962 completed April 10, 2026, 7:20 a.m.
NED1 Entity disambiguation (via context triple) batch_69ef8397a4ac8190a71dfdd53bfa168a completed April 27, 2026, 3:41 p.m.
Created at: April 8, 2026, 9:40 p.m.