Triple

T21807545
Position Surface form Disambiguated ID Type / Status
Subject Mānoa Falls E538385 entity
Predicate nameContains P5298 FINISHED
Object Mānoa 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: Mānoa | Statement: [Mānoa Falls, nameContains, Mānoa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mānoa
Context triple: [Mānoa Falls, nameContains, Mānoa]
  • A. Mānoa chosen
    Mānoa is a verdant residential valley and neighborhood in Honolulu known for its frequent rainbows, historic homes, and the main campus of the University of Hawaiʻi.
  • B. Nānākuli
    Nānākuli is a coastal community on the leeward side of Oʻahu in Hawaii, known for its strong Native Hawaiian presence and scenic beaches.
  • C. Kaliua
    Kaliua is a town in western Tanzania that serves as the administrative and commercial center of Kaliua District in Tabora Region.
  • D. Kailua
    Kailua is a coastal town on the windward side of Oahu in Hawaii, known for its scenic beaches and relaxed residential atmosphere.
  • E. Kailua-Kona
    Kailua-Kona is a coastal town on the west side of Hawaii's Big Island known for its sunny beaches, historic sites, coffee farms, and role as a major tourist and commercial center.
  • 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_69e0c473f0f8819086c9d1b4a143bd67 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69f07803b4888190af06bf7a90198f60 completed April 28, 2026, 9:04 a.m.
Created at: April 16, 2026, 6:53 p.m.