Triple

T28120573
Position Surface form Disambiguated ID Type / Status
Subject Wilder Avenue E710771 entity
Predicate hasIntersectionWith P13379 FINISHED
Object Piikoi Street
Piikoi Street is a major north–south thoroughfare in Honolulu, Hawaii, running through urban neighborhoods and connecting residential areas with key city routes.
E1831122 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: Piikoi Street | Statement: [Wilder Avenue, hasIntersectionWith, Piikoi Street]
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: Piikoi Street
Triple: [Wilder Avenue, hasIntersectionWith, Piikoi Street]
Generated description
Piikoi Street is a major north–south thoroughfare in Honolulu, Hawaii, running through urban neighborhoods and connecting residential areas with key city routes.

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_69ef9b72f63081909dfbc2c1ddae86c6 completed April 27, 2026, 5:22 p.m.
NER Named-entity recognition batch_69f640f73d9481909a07574a7db092eb completed May 2, 2026, 6:22 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1ccf12592c81909fc7c6127a50ca7d completed June 1, 2026, 12:15 a.m.
NEDg Description generation batch_6a1cd03986848190a322d5273d0164d0 completed June 1, 2026, 12:20 a.m.
NED2 Entity disambiguation (via description) batch_6a24946ccd908190ae144fbc7010aca9 completed June 6, 2026, 9:43 p.m.
Created at: April 27, 2026, 9:16 p.m.