Triple

T5813410
Position Surface form Disambiguated ID Type / Status
Subject Mater Dei Catholic College E128924 entity
Predicate locatedIn P40 FINISHED
Object Wagga Wagga E20750 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: Wagga Wagga | Statement: [Mater Dei Catholic College, locatedIn, Wagga Wagga]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wagga Wagga
Context triple: [Mater Dei Catholic College, locatedIn, Wagga Wagga]
  • A. Wagga Wagga chosen
    Wagga Wagga is a major regional city in New South Wales, Australia, known as an important agricultural, military, and transport hub in the Riverina region.
  • B. Katoomba
    Katoomba is a popular town in New South Wales, Australia, known as the main tourist hub of the Blue Mountains with attractions like the Three Sisters rock formation and scenic bushwalking trails.
  • C. Albury
    Albury is a small rural village and civil parish in Hertfordshire, England, known for its historic church and countryside setting.
  • D. Albury
    Albury is a major regional city in New South Wales, Australia, located on the border with Victoria and known as a key commercial and transport hub of the Murray River region.
  • E. Deniliquin
    Deniliquin is a rural town in southern New South Wales, Australia, known for its agricultural industry and annual ute muster festival.
  • 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_69c0084788848190bcf71f6bc5d71597 completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c03360749481908d42fde7a74a754f completed March 22, 2026, 6:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69c107e64edc819080b3ebf9b9137749 completed March 23, 2026, 9:29 a.m.
Created at: March 22, 2026, 3:52 p.m.