Triple

T37498301
Position Surface form Disambiguated ID Type / Status
Subject Higashi-Hennazaki Cape E931889 entity
Predicate hasStructure P35 FINISHED
Object Higashi-Hennazaki Lighthouse
Higashi-Hennazaki Lighthouse is a coastal beacon on Miyako Island in Okinawa, Japan, known for its panoramic ocean views and role in guiding ships through the surrounding waters.
E2228154 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: Higashi-Hennazaki Lighthouse | Statement: [Higashi-Hennazaki Cape, hasStructure, Higashi-Hennazaki Lighthouse]
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: Higashi-Hennazaki Lighthouse
Triple: [Higashi-Hennazaki Cape, hasStructure, Higashi-Hennazaki Lighthouse]
Generated description
Higashi-Hennazaki Lighthouse is a coastal beacon on Miyako Island in Okinawa, Japan, known for its panoramic ocean views and role in guiding ships through the surrounding waters.

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_69f76ec457a4819094eeb3aed9baac11 completed May 3, 2026, 3:50 p.m.
NER Named-entity recognition batch_69fba382bb60819083b5dd86df0c4322 completed May 6, 2026, 8:24 p.m.
NED1 Entity disambiguation (via context triple) batch_6a408c4d8a988190a76e56be75b1bdb2 completed June 28, 2026, 2:51 a.m.
NEDg Description generation batch_6a408d2e0fa08190b1cf565f595ed784 completed June 28, 2026, 2:55 a.m.
NED2 Entity disambiguation (via description) batch_6a408d9a88588190acbfd23182ba0353 completed June 28, 2026, 2:57 a.m.
Created at: May 3, 2026, 4:17 p.m.