Triple

T24333502
Position Surface form Disambiguated ID Type / Status
Subject Kubor Range E613312 entity
Predicate partOf P40 FINISHED
Object Papua New Guinea Highlands region
The Papua New Guinea Highlands region is a mountainous inland area known for its rugged terrain, rich biodiversity, and diverse indigenous cultures.
E312325 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 Highlands region | Statement: [Kubor Range, partOf, Papua New Guinea Highlands region]
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 Highlands region
Triple: [Kubor Range, partOf, Papua New Guinea Highlands region]
Generated description
The Papua New Guinea Highlands region is a mountainous inland area known for its rugged terrain, rich biodiversity, and diverse indigenous cultures.

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_69e2d7db6d5c819091194918157a7c1f completed April 18, 2026, 1:01 a.m.
NER Named-entity recognition batch_69f292f381b08190b529a765a5d5e89b completed April 29, 2026, 11:23 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0fd65b7c908190b416b01e5f744d67 completed May 22, 2026, 4:06 a.m.
NEDg Description generation batch_6a0fd7124c4481908d899a9292f534e9 completed May 22, 2026, 4:09 a.m.
NED2 Entity disambiguation (via description) batch_6a0fd7c16e788190a760642a991c421e completed May 22, 2026, 4:12 a.m.
Created at: April 18, 2026, 1:56 a.m.