Triple

T36208247
Position Surface form Disambiguated ID Type / Status
Subject Dudjom Rinpoche E1047459 entity
Predicate teacherOf P48 FINISHED
Object Tulku Thondup Rinpoche
Tulku Thondup Rinpoche is a Tibetan Buddhist scholar and meditation master known for his writings on healing, happiness, and the Dzogchen tradition.
E2235794 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: Tulku Thondup Rinpoche | Statement: [Dudjom Rinpoche, teacherOf, Tulku Thondup Rinpoche]
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: Tulku Thondup Rinpoche
Triple: [Dudjom Rinpoche, teacherOf, Tulku Thondup Rinpoche]
Generated description
Tulku Thondup Rinpoche is a Tibetan Buddhist scholar and meditation master known for his writings on healing, happiness, and the Dzogchen tradition.

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_69f76e4214748190a76c986d2a1838c2 completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69f7b55053a08190a14c7d52f81f4825 completed May 3, 2026, 8:51 p.m.
NED1 Entity disambiguation (via context triple) batch_6a40afc52bbc81909f068dbb4a16dd89 completed June 28, 2026, 5:23 a.m.
NEDg Description generation batch_6a40b0813c188190b68fcf732f0406e3 completed June 28, 2026, 5:26 a.m.
NED2 Entity disambiguation (via description) batch_6a40b10e1c7881909c83962729029f0a completed June 28, 2026, 5:28 a.m.
Created at: May 3, 2026, 4:09 p.m.