Triple

T6300533
Position Surface form Disambiguated ID Type / Status
Subject Molokai Airport E141241 entity
Predicate cityServed P82 FINISHED
Object Kaunakakai E139694 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: Kaunakakai | Statement: [Molokai Airport, cityServed, Kaunakakai]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kaunakakai
Context triple: [Molokai Airport, cityServed, Kaunakakai]
  • A. Kaunakakai chosen
    Kaunakakai is the main town and commercial center of the Hawaiian island of Molokaʻi, known for its small-town character and historic harbor.
  • B. Kawaikini
    Kawaikini is the highest peak on the Hawaiian island of Kauaʻi, located in the island’s central, rainforest-covered interior.
  • C. Taneti Maamau
    Taneti Maamau is a Kiribati politician who has served as the country's president, known for his pro-China foreign policy stance and focus on economic development and climate resilience.
  • D. Tanimaiaki
    Tanimaiaki is a settlement on the atoll of Abemama in the island nation of Kiribati in the central Pacific Ocean.
  • E. Punasa
    Punasa is a town in Madhya Pradesh, India, known for its proximity to the major Indira Sagar Dam on the Narmada River.
  • 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_69c008cf0ad4819095def81e2bd42f9f completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c0645bb41481909294b06e2b3e1845 completed March 22, 2026, 9:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69c5e42f38bc819086a3e66a83ffc792 completed March 27, 2026, 1:58 a.m.
Created at: March 22, 2026, 4:27 p.m.