Triple

T25221372
Position Surface form Disambiguated ID Type / Status
Subject Hāmākua District E631972 entity
Predicate contains P35 FINISHED
Object Nīnole
Nīnole is a small coastal community on the Big Island of Hawaiʻi known for its rural character, lush landscapes, and scenic ocean views.
E1736133 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: Nīnole | Statement: [Hāmākua District, contains, Nīnole]
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Nīnole
Triple: [Hāmākua District, contains, Nīnole]
Generated description
Nīnole is a small coastal community on the Big Island of Hawaiʻi known for its rural character, lush landscapes, and scenic ocean views.

Provenance (5 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_69e75a8e0f688190a7aebe9a4815e25b completed April 21, 2026, 11:07 a.m.
NER Named-entity recognition batch_69f47cc0578881909ed1e40c09fdc38d completed May 1, 2026, 10:13 a.m.
NED1 Entity disambiguation (via context triple) batch_6a11ebe8b6148190bd3ffd2a7a7fa011 completed May 23, 2026, 6:03 p.m.
NEDg Description generation batch_6a11efbbc08081908061e4a0703c16e8 completed May 23, 2026, 6:19 p.m.
NED2 Entity disambiguation (via description) batch_6a11f014db348190a497218396a16e4b completed May 23, 2026, 6:21 p.m.
Created at: April 21, 2026, 1:03 p.m.