Triple

T20769404
Position Surface form Disambiguated ID Type / Status
Subject Tasman Bay E511183 entity
Predicate hasNearbyIsland P970 FINISHED
Object Haulashore Island
Haulashore Island is a small, low-lying island near Nelson, New Zealand, known for its role as a former part of the mainland and as a popular spot for local recreation and wildlife.
E2287206 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: Haulashore Island | Statement: [Tasman Bay, hasNearbyIsland, Haulashore 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: Haulashore Island
Triple: [Tasman Bay, hasNearbyIsland, Haulashore Island]
Generated description
Haulashore Island is a small, low-lying island near Nelson, New Zealand, known for its role as a former part of the mainland and as a popular spot for local recreation and wildlife.

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_69e0b4ca01148190ac018e57e0cab46f completed April 16, 2026, 10:07 a.m.
NER Named-entity recognition batch_69e6c265f7dc8190a084e35d38d2783a completed April 21, 2026, 12:18 a.m.
NED1 Entity disambiguation (via context triple) batch_6a476c7837c08190bfa9d925397b06bf completed July 3, 2026, 8:02 a.m.
NEDg Description generation batch_6a476cff751c81909265b5a6ad4ebac3 completed July 3, 2026, 8:04 a.m.
NED2 Entity disambiguation (via description) batch_6a476d9199a481909654a5576f29fab3 completed July 3, 2026, 8:06 a.m.
Created at: April 16, 2026, 12:36 p.m.