Triple

T13484983
Position Surface form Disambiguated ID Type / Status
Subject Kapolei High School E318471 entity
Predicate servesLocality P26183 FINISHED
Object Ewa Plain E975013 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: Ewa Plain | Statement: [Kapolei High School, servesLocality, Ewa Plain]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ewa Plain
Context triple: [Kapolei High School, servesLocality, Ewa Plain]
  • A. Ewa Plain chosen
    Ewa Plain is a coastal lowland region on the island of Oʻahu in Hawaii, known for its dry climate, coral limestone foundation, and historical use for sugarcane plantations and urban development.
  • B. Tivoli plain
    The Tivoli plain is a lowland area near the town of Tivoli in central Italy, known for its fertile terrain and historical significance in the Roman countryside.
  • C. Çarşamba Plain
    Çarşamba Plain is a fertile agricultural lowland in northern Turkey, situated near the Black Sea coast in Samsun Province.
  • D. Iyo Plain
    The Iyo Plain is a fertile coastal lowland in western Shikoku known as one of Ehime Prefecture’s main agricultural and settlement areas.
  • E. Soest plain
    The Soest plain is a fertile lowland region in North Rhine-Westphalia, Germany, known for its intensive agriculture and historically significant settlement landscape.
  • 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_69d806b6bfec819089222715b2e86c8e completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69dbaf3a15b48190b63fb59e926a97ae completed April 12, 2026, 2:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7463715dc8190a70a17b3ea661006 completed May 3, 2026, 12:57 p.m.
Created at: April 9, 2026, 9:42 p.m.