Triple

T21787636
Position Surface form Disambiguated ID Type / Status
Subject Hokkaido northern coast E537881 entity
Predicate hasNearbyIsland P970 FINISHED
Object Teuri Island
Teuri Island is a small island off the northern coast of Hokkaido, Japan, renowned as a major seabird breeding site and wildlife observation destination.
E2163184 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: Teuri Island | Statement: [Hokkaido northern coast, hasNearbyIsland, Teuri Island]
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: Teuri Island
Triple: [Hokkaido northern coast, hasNearbyIsland, Teuri Island]
Generated description
Teuri Island is a small island off the northern coast of Hokkaido, Japan, renowned as a major seabird breeding site and wildlife observation destination.

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_69e0c47198f881908cb0d237266c10e9 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69f0621c68588190977891055e80a499 completed April 28, 2026, 7:30 a.m.
NED1 Entity disambiguation (via context triple) batch_6a38b6d7f6648190ad289363f5219441 completed June 22, 2026, 4:15 a.m.
NEDg Description generation batch_6a38b822a2a481909a16755875adedc0 completed June 22, 2026, 4:20 a.m.
NED2 Entity disambiguation (via description) batch_6a38b8a713a481908bccea46167911fc completed June 22, 2026, 4:23 a.m.
Created at: April 16, 2026, 6:52 p.m.