Triple

T25284217
Position Surface form Disambiguated ID Type / Status
Subject Makwanpur District E633893 entity
Predicate hasMountainRange P651 FINISHED
Object Chure Range
The Chure Range is a low, geologically young Himalayan foothill range in Nepal that forms part of the Siwalik Hills and plays a key role in the region’s ecology and watershed systems.
E1695912 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: Chure Range | Statement: [Makwanpur District, hasMountainRange, Chure Range]
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: Chure Range
Triple: [Makwanpur District, hasMountainRange, Chure Range]
Generated description
The Chure Range is a low, geologically young Himalayan foothill range in Nepal that forms part of the Siwalik Hills and plays a key role in the region’s ecology and watershed systems.

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_69e75a9402fc81909362ca85277c06d9 completed April 21, 2026, 11:08 a.m.
NER Named-entity recognition batch_69f48e0800a881909bf6099d120338a5 completed May 1, 2026, 11:27 a.m.
NED1 Entity disambiguation (via context triple) batch_6a10d9e414848190a387e80a98ed9dea completed May 22, 2026, 10:34 p.m.
NEDg Description generation batch_6a10da9b545081908e5837e1de98fe40 completed May 22, 2026, 10:37 p.m.
NED2 Entity disambiguation (via description) batch_6a10db0f7a608190ae0c34f6f6ce0ad8 completed May 22, 2026, 10:39 p.m.
Created at: April 21, 2026, 1:19 p.m.