Triple

T25134987
Position Surface form Disambiguated ID Type / Status
Subject Interior Highlands of Borneo E629631 entity
Predicate contains P35 FINISHED
Object Usun Apau Plateau
Usun Apau Plateau is a remote volcanic highland region in central Borneo known for its rugged terrain, montane forests, and relative ecological isolation.
E1675847 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: Usun Apau Plateau | Statement: [Interior Highlands of Borneo, contains, Usun Apau Plateau]
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: Usun Apau Plateau
Triple: [Interior Highlands of Borneo, contains, Usun Apau Plateau]
Generated description
Usun Apau Plateau is a remote volcanic highland region in central Borneo known for its rugged terrain, montane forests, and relative ecological isolation.

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_69e2ff338250819096ff6c8892804389 completed April 18, 2026, 3:49 a.m.
NER Named-entity recognition batch_69f465febf508190a350d9e1f9b4dda5 completed May 1, 2026, 8:36 a.m.
NED1 Entity disambiguation (via context triple) batch_6a1075be9b388190b7099b139602f5cc completed May 22, 2026, 3:26 p.m.
NEDg Description generation batch_6a1076991b208190945d037fd9eef5f2 completed May 22, 2026, 3:30 p.m.
NED2 Entity disambiguation (via description) batch_6a1077d01fa08190b5439eba879538ef completed May 22, 2026, 3:35 p.m.
Created at: April 18, 2026, 6:29 a.m.