Triple

T37735338
Position Surface form Disambiguated ID Type / Status
Subject Sandokai E940261 entity
Predicate commentedOnBy P11804 FINISHED
Object Shohaku Okumura
Shohaku Okumura is a contemporary Sōtō Zen priest, teacher, and translator known for his detailed commentaries on classic Zen texts and for founding the Sanshin Zen Community in Bloomington, Indiana.
E2245259 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: Shohaku Okumura | Statement: [Sandokai, commentedOnBy, Shohaku Okumura]
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: Shohaku Okumura
Triple: [Sandokai, commentedOnBy, Shohaku Okumura]
Generated description
Shohaku Okumura is a contemporary Sōtō Zen priest, teacher, and translator known for his detailed commentaries on classic Zen texts and for founding the Sanshin Zen Community in Bloomington, Indiana.

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_69f76edefd048190a32212c5c3919531 completed May 3, 2026, 3:50 p.m.
NER Named-entity recognition batch_69fbae9a390481909d903a0c91bc5399 completed May 6, 2026, 9:11 p.m.
NED1 Entity disambiguation (via context triple) batch_6a40fb6c45d88190910f4bb96c22c90a completed June 28, 2026, 10:46 a.m.
NEDg Description generation batch_6a40fc690fe08190b4ceaadfe93be2a3 completed June 28, 2026, 10:50 a.m.
NED2 Entity disambiguation (via description) batch_6a40fce18ec08190946c064d27fcf5ad completed June 28, 2026, 10:52 a.m.
Created at: May 3, 2026, 4:18 p.m.