Triple

T26736421
Position Surface form Disambiguated ID Type / Status
Subject East Papuan languages E674124 entity
Predicate includesLanguage P2177 FINISHED
Object Nasioi language
The Nasioi language is an indigenous Papuan language spoken primarily by the Nasioi people of central and southern Bougainville in Papua New Guinea.
E1755881 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: Nasioi language | Statement: [East Papuan languages, includesLanguage, Nasioi language]
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: Nasioi language
Triple: [East Papuan languages, includesLanguage, Nasioi language]
Generated description
The Nasioi language is an indigenous Papuan language spoken primarily by the Nasioi people of central and southern Bougainville in Papua New Guinea.

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_69eecda57ab481909424e98f2835e7d8 completed April 27, 2026, 2:44 a.m.
NER Named-entity recognition batch_69f61844d7f8819081080f687999b77a completed May 2, 2026, 3:29 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1247dbd09c81908d11c4e64baec8c4 completed May 24, 2026, 12:35 a.m.
NEDg Description generation batch_6a1248569490819085cd93e8cf9bf014 completed May 24, 2026, 12:37 a.m.
NED2 Entity disambiguation (via description) batch_6a1248d46e28819096dc8167c0a5bc46 completed May 24, 2026, 12:39 a.m.
Created at: April 27, 2026, 3:47 a.m.