Triple

T14826084
Position Surface form Disambiguated ID Type / Status
Subject Temora Airport E348574 entity
Predicate town P3385 FINISHED
Object Temora E11960 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: Temora | Statement: [Temora Airport, town, Temora]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Temora
Context triple: [Temora Airport, town, Temora]
  • A. Temora chosen
    Temora is a rural town in the Riverina region of New South Wales, Australia, known for its rich agricultural base and aviation heritage.
  • B. Temora
    Temora is an epic poem attributed to the legendary bard Ossian, known for its melancholic tone and romanticized depiction of ancient Gaelic heroism.
  • C. Soluntum
    Soluntum was an important ancient Punic city on the northern coast of Sicily, known as a major center of Carthaginian presence on the island.
  • D. Glanum
    Glanum is an ancient Greco-Roman city in southern France known for its well-preserved ruins and monumental architecture.
  • E. Argiletum
    Argiletum was an ancient street in Rome that connected the Roman Forum to the Subura district and later became partly occupied by the Forum of Nerva.
  • 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_69d822eb8f588190bf53445e730a934f completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69ded0713700819097bbb0352650984b completed April 14, 2026, 11:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe72a6b4388190b83bdecb217b9b18 completed May 8, 2026, 11:32 p.m.
Created at: April 10, 2026, 1:51 a.m.