Triple

T18182376
Position Surface form Disambiguated ID Type / Status
Subject Nanbu clan E435320 entity
Predicate notableLeader P304 FINISHED
Object Nanbu Toshiyuki
Nanbu Toshiyuki was a prominent Japanese daimyō of the Nanbu clan who led the Morioka Domain during the late Edo period.
E1926943 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: Nanbu Toshiyuki | Statement: [Nanbu clan, notableLeader, Nanbu Toshiyuki]
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: Nanbu Toshiyuki
Triple: [Nanbu clan, notableLeader, Nanbu Toshiyuki]
Generated description
Nanbu Toshiyuki was a prominent Japanese daimyō of the Nanbu clan who led the Morioka Domain during the late Edo period.

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_69d8b90c7ec081909b4694ccecb449c6 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4dffc432c8190af53da5256dc476c completed April 19, 2026, 2 p.m.
NED1 Entity disambiguation (via context triple) batch_6a2870be0b8c8190b3c16d534c995558 completed June 9, 2026, 7:59 p.m.
NEDg Description generation batch_6a2878ea68388190a662e27e45537c93 completed June 9, 2026, 8:34 p.m.
NED2 Entity disambiguation (via description) batch_6a28793daecc819097218352545caad0 completed June 9, 2026, 8:36 p.m.
Created at: April 10, 2026, 10:31 a.m.