Triple

T35437098
Position Surface form Disambiguated ID Type / Status
Subject Papua New Guinea parliamentary constituencies E1024239 entity
Predicate relatedTo P37 FINISHED
Object Papua New Guinea provinces
Papua New Guinea provinces are the country’s primary subnational administrative divisions, each governed by its own provincial authorities and encompassing multiple local-level areas and constituencies.
E2139731 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: Papua New Guinea provinces | Statement: [Papua New Guinea parliamentary constituencies, relatedTo, Papua New Guinea provinces]
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: Papua New Guinea provinces
Triple: [Papua New Guinea parliamentary constituencies, relatedTo, Papua New Guinea provinces]
Generated description
Papua New Guinea provinces are the country’s primary subnational administrative divisions, each governed by its own provincial authorities and encompassing multiple local-level areas and constituencies.

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_69f76df743c48190aecb6dd79efb0d95 completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f795bd7d40819087be4fe0e15a5ed3 completed May 3, 2026, 6:36 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3836c27d048190b3f86b5bdc8a1b0e completed June 21, 2026, 7:08 p.m.
NEDg Description generation batch_6a3837384524819091f87708dfb5190d completed June 21, 2026, 7:10 p.m.
NED2 Entity disambiguation (via description) batch_6a3837a3217081909acdb8bdcf9506ca completed June 21, 2026, 7:12 p.m.
Created at: May 3, 2026, 4:04 p.m.