Triple

T17472129
Position Surface form Disambiguated ID Type / Status
Subject Port Adelaide-Enfield E425443 entity
Predicate contains P35 FINISHED
Object Taperoo 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: Taperoo | Statement: [Port Adelaide-Enfield, contains, Taperoo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Taperoo
Context triple: [Port Adelaide-Enfield, contains, Taperoo]
  • A. Taperoo chosen
    Taperoo is a coastal suburb in Adelaide, South Australia, known for its residential areas and proximity to Gulf St Vincent.
  • B. Tupe
    Tupe is a small Andean town in Peru known for preserving the unique Jaqaru indigenous language and culture.
  • C. Tapaz
    Tapaz is a landlocked agricultural municipality in the province of Capiz on Panay Island in the Philippines, known for its rural landscapes and river valleys.
  • D. Tarouca
    Tarouca is a municipality in Portugal’s Douro region, known for its historic monasteries, vineyards, and scenic river valley landscapes.
  • E. Tapalpa
    Tapalpa is a picturesque mountain town in the Mexican state of Jalisco, known for its colonial architecture, pine forests, and outdoor recreation.
  • 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_69d889dbc2e88190b18ea6115e819258 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e451b8a51081908d94bebe2417e3d3 completed April 19, 2026, 3:53 a.m.
Created at: April 10, 2026, 5:47 a.m.