Triple

T37017397
Position Surface form Disambiguated ID Type / Status
Subject Taihō E916119 entity
Predicate administrativeReformType P98268 FINISHED
Object codification of offices and ranks LITERAL 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: codification of offices and ranks | Statement: [Taihō, administrativeReformType, codification of offices and ranks]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: administrativeReformType
Context triple: [Taihō, administrativeReformType, codification of offices and ranks]
  • A. typeOfReforms chosen
    Indicates the specific kinds or categories of reforms associated with an entity or situation.
  • B. reform
    Indicates bringing about significant changes to an existing system, practice, or entity in order to improve or correct it.
  • C. typeOfReformBody
    Indicates that one entity is a reform body that is classified as a specific type or category of reform body represented by the other entity.
  • D. subjectToReformBy
    Indicates that an entity is undergoing or designated for changes, improvements, or restructuring carried out by another entity.
  • E. isReformOriented
    Indicates that an entity is oriented toward initiating, supporting, or implementing reforms or improvements within a system, policy, or practice.
  • F. None of above.

Provenance (3 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_69f76e920dc48190acb6bb7ebc4dffab completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69fe72dca2f08190beff17de3d2aada6 completed May 8, 2026, 11:33 p.m.
PD Predicate disambiguation batch_69fe70bca8d08190b810e1e616ceac44 completed May 8, 2026, 11:24 p.m.
Created at: May 3, 2026, 4:14 p.m.