Triple

T20130759
Position Surface form Disambiguated ID Type / Status
Subject Camden Haven district E490883 entity
Predicate hasTown P847 FINISHED
Object Lake Cathie 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: Lake Cathie | Statement: [Camden Haven district, hasTown, Lake Cathie]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lake Cathie
Context triple: [Camden Haven district, hasTown, Lake Cathie]
  • A. Lake Cathie chosen
    Lake Cathie is a small coastal town and lagoon system in New South Wales, Australia, known for its beaches, fishing, and relaxed holiday atmosphere.
  • B. Lake Clementine
    Lake Clementine is a scenic reservoir on the North Fork of the American River in California, popular for boating, kayaking, and lakeside recreation.
  • C. Lake Secor
    Lake Secor is a small residential lake community in the town of Carmel in Putnam County, New York.
  • D. Lake Bonham
    Lake Bonham is a man-made reservoir in Fannin County, Texas, primarily used for municipal water supply and recreational activities such as fishing and boating.
  • E. Lake Matheson
    Lake Matheson is a famous mirror lake on New Zealand’s South Island, renowned for its reflective views of Aoraki/Mount Cook and Mount Tasman.
  • 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_69da62651a0c8190a3e05e95e056a66b completed April 11, 2026, 3:01 p.m.
NER Named-entity recognition batch_69e6676183dc8190b65d0def681aaa1e completed April 20, 2026, 5:50 p.m.
Created at: April 11, 2026, 11:31 p.m.