Triple

T28483078
Position Surface form Disambiguated ID Type / Status
Subject Mani Rimdu festival E720746 entity
Predicate mainLocation P3231 FINISHED
Object Chiwong Monastery
Chiwong Monastery is a Tibetan Buddhist monastery in Nepal’s Solu region, renowned as a principal venue for the Mani Rimdu festival.
E1837545 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: Chiwong Monastery | Statement: [Mani Rimdu festival, mainLocation, Chiwong Monastery]
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: Chiwong Monastery
Triple: [Mani Rimdu festival, mainLocation, Chiwong Monastery]
Generated description
Chiwong Monastery is a Tibetan Buddhist monastery in Nepal’s Solu region, renowned as a principal venue for the Mani Rimdu festival.

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_69f01a5a47148190b0a7e111bc432e0a completed April 28, 2026, 2:24 a.m.
NER Named-entity recognition batch_69f64f0e06c481909cb71bdc8deecbfe completed May 2, 2026, 7:22 p.m.
NED1 Entity disambiguation (via context triple) batch_6a24bb7fe9b08190b372914781ff7c92 completed June 7, 2026, 12:29 a.m.
NEDg Description generation batch_6a24bf95145c81908c8b06ac4c17c086 completed June 7, 2026, 12:47 a.m.
NED2 Entity disambiguation (via description) batch_6a24c40832a881908ca8c2d0b09b1458 completed June 7, 2026, 1:06 a.m.
Created at: April 28, 2026, 2:56 a.m.