Triple

T2907979
Position Surface form Disambiguated ID Type / Status
Subject Fannie Bay E63611 entity
Predicate adjacentTo P224 FINISHED
Object Parap E60401 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: Parap | Statement: [Fannie Bay, adjacentTo, Parap]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Parap
Context triple: [Fannie Bay, adjacentTo, Parap]
  • A. Parap chosen
    Parap is an inner-city suburb of Darwin in Australia's Northern Territory, known for its popular weekend markets and tropical, laid-back atmosphere.
  • B. Parag
    Parag is a given name most notably associated with Parag Agrawal, the former CEO of Twitter.
  • C. Parl
    Parl is the commonly used abbreviation for the Parliament of Singapore, the country's unicameral legislative body.
  • D. The Paras
    The Paras are an elite airborne infantry regiment of the British Army renowned for their rigorous training, rapid deployment capabilities, and distinguished combat history.
  • E. Pan
    Pan is a 1894 novel by Norwegian author Knut Hamsun, known for its lyrical portrayal of nature and its psychologically intense depiction of love and jealousy.
  • 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_69ab4c44ab448190b9411324e8a1fc1d completed March 6, 2026, 9:51 p.m.
NER Named-entity recognition batch_69abe0d1dcf881909b3ae58d7cdfd9cd completed March 7, 2026, 8:24 a.m.
NED1 Entity disambiguation (via context triple) batch_69b056173a988190be02619d909cdb25 completed March 10, 2026, 5:34 p.m.
Created at: March 6, 2026, 10:11 p.m.