Triple

T19739684
Position Surface form Disambiguated ID Type / Status
Subject Tristan Honsinger E474080 entity
Predicate associatedAct P37 FINISHED
Object Toshinori Kondo
Toshinori Kondo was a Japanese avant-garde jazz and free improvisation trumpeter known for his innovative use of electronics and collaborations across experimental and world music scenes.
E2293231 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: Toshinori Kondo | Statement: [Tristan Honsinger, associatedAct, Toshinori Kondo]
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: Toshinori Kondo
Triple: [Tristan Honsinger, associatedAct, Toshinori Kondo]
Generated description
Toshinori Kondo was a Japanese avant-garde jazz and free improvisation trumpeter known for his innovative use of electronics and collaborations across experimental and world music scenes.

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_69d8e517ebd48190979ee76723bcfadf completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e651607e388190bbb2aaed252820fe completed April 20, 2026, 4:16 p.m.
NED1 Entity disambiguation (via context triple) batch_6a7a7be24ee081908954e90d84637f65 completed Aug. 11, 2026, 1:33 a.m.
NEDg Description generation batch_6a7a7cabba6881909ff81c92c0b88809 completed Aug. 11, 2026, 1:36 a.m.
NED2 Entity disambiguation (via description) batch_6a7a7cc632408190b45997db6b1d3347 completed Aug. 11, 2026, 1:37 a.m.
Created at: April 10, 2026, 1:47 p.m.