Triple

T37262504
Position Surface form Disambiguated ID Type / Status
Subject Pelsaert Group E924291 entity
Predicate hasIsland P970 FINISHED
Object Gun Island
Gun Island is a small, remote island within Western Australia’s Pelsaert Group, known primarily as part of the Houtman Abrolhos archipelago and for its surrounding rich marine and bird life.
E2286933 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: Gun Island | Statement: [Pelsaert Group, hasIsland, Gun 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: Gun Island
Triple: [Pelsaert Group, hasIsland, Gun Island]
Generated description
Gun Island is a small, remote island within Western Australia’s Pelsaert Group, known primarily as part of the Houtman Abrolhos archipelago and for its surrounding rich marine and bird life.

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_69f76eabd6c481909d414a80a1345c98 completed May 3, 2026, 3:50 p.m.
NER Named-entity recognition batch_69fb37300aac8190bf19c7ecc06b6dfd completed May 6, 2026, 12:42 p.m.
NED1 Entity disambiguation (via context triple) batch_6a4744f36328819083ee69f90139cea6 completed July 3, 2026, 5:13 a.m.
NEDg Description generation batch_6a47472fc34c819088626151612f1800 completed July 3, 2026, 5:22 a.m.
NED2 Entity disambiguation (via description) batch_6a4747b982248190af2a972d0973e683 completed July 3, 2026, 5:25 a.m.
Created at: May 3, 2026, 4:15 p.m.