Triple

T23916194
Position Surface form Disambiguated ID Type / Status
Subject Bosavi languages E602088 entity
Predicate region P40 FINISHED
Object Mount Bosavi area
The Mount Bosavi area is a remote, mountainous region of Papua New Guinea known for its rich linguistic diversity and unique ecosystems surrounding the extinct volcano Mount Bosavi.
E1608868 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: Mount Bosavi area | Statement: [Bosavi languages, region, Mount Bosavi area]
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: Mount Bosavi area
Triple: [Bosavi languages, region, Mount Bosavi area]
Generated description
The Mount Bosavi area is a remote, mountainous region of Papua New Guinea known for its rich linguistic diversity and unique ecosystems surrounding the extinct volcano Mount Bosavi.

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_69e2953a187081908346a9f36e85fc98 completed April 17, 2026, 8:16 p.m.
NER Named-entity recognition batch_69f1ce9a744c819080bd30176b8de9a0 completed April 29, 2026, 9:25 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0f76399a648190b5e75eab7de7cea7 completed May 21, 2026, 9:16 p.m.
NEDg Description generation batch_6a0f76cd32688190ac032b5b79dba0b8 completed May 21, 2026, 9:19 p.m.
NED2 Entity disambiguation (via description) batch_6a0f78c5e978819086792ca6d9835ff9 completed May 21, 2026, 9:27 p.m.
Created at: April 17, 2026, 8:40 p.m.