Triple

T28127460
Position Surface form Disambiguated ID Type / Status
Subject Drepung Monastery E710967 entity
Predicate monasticColleges P164061 FINISHED
Object Ngagpa College
Ngagpa College is one of the traditional scholastic institutions within Drepung Monastery, dedicated to advanced study and practice of Tibetan Buddhist philosophy and ritual.
E1803291 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: Ngagpa College | Statement: [Drepung Monastery, monasticColleges, Ngagpa College]
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: Ngagpa College
Triple: [Drepung Monastery, monasticColleges, Ngagpa College]
Generated description
Ngagpa College is one of the traditional scholastic institutions within Drepung Monastery, dedicated to advanced study and practice of Tibetan Buddhist philosophy and ritual.

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_69ef9b73bd288190a21ae3d6aa14f386 completed April 27, 2026, 5:22 p.m.
NER Named-entity recognition batch_69f64cb36ed88190973a4790577762eb completed May 2, 2026, 7:12 p.m.
NED1 Entity disambiguation (via context triple) batch_6a15c939f6fc8190b4e0e651d73ad18a completed May 26, 2026, 4:24 p.m.
NEDg Description generation batch_6a15cab48b3c81908fae4b6aa2e03453 completed May 26, 2026, 4:30 p.m.
NED2 Entity disambiguation (via description) batch_6a15cb26ac548190b72fb86d3d6c7c10 completed May 26, 2026, 4:32 p.m.
Created at: April 27, 2026, 9:21 p.m.