Triple

T24756701
Position Surface form Disambiguated ID Type / Status
Subject Uneapa language E619306 entity
Predicate spokenIn P2266 FINISHED
Object Uneapa Island
Uneapa Island is a small island in Papua New Guinea’s Bismarck Archipelago, home to the Uneapa-speaking community and known for its distinct local culture.
E2293638 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: Uneapa Island | Statement: [Uneapa language, spokenIn, Uneapa 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: Uneapa Island
Triple: [Uneapa language, spokenIn, Uneapa Island]
Generated description
Uneapa Island is a small island in Papua New Guinea’s Bismarck Archipelago, home to the Uneapa-speaking community and known for its distinct local culture.

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_69e2fabb349881908a13a212a0221a63 completed April 18, 2026, 3:30 a.m.
NER Named-entity recognition batch_69f41078fb788190bc6c18ed85b45049 completed May 1, 2026, 2:31 a.m.
NED1 Entity disambiguation (via context triple) batch_6a7ae7c101488190a192ba9bb8570486 completed Aug. 11, 2026, 9:13 a.m.
NEDg Description generation batch_6a7ae80cfb2081909b39746d64d4a675 completed Aug. 11, 2026, 9:14 a.m.
NED2 Entity disambiguation (via description) batch_6a7ae961cc708190ac3b20e200605c4e completed Aug. 11, 2026, 9:20 a.m.
Created at: April 18, 2026, 4:26 a.m.