Triple

T186493
Position Surface form Disambiguated ID Type / Status
Subject Nihon-koku Kenpō E3991 entity
Predicate amendmentRequires P6723 FINISHED
Object two-thirds majority in both houses of the Diet 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: two-thirds majority in both houses of the Diet | Statement: [Nihon-koku Kenpō, amendmentRequires, two-thirds majority in both houses of the Diet]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: amendmentRequires
Context triple: [Nihon-koku Kenpō, amendmentRequires, two-thirds majority in both houses of the Diet]
  • A. amendmentCount
    Indicates the number of amendments that have been made to a given item, document, or entity.
  • B. amendedBy
    Indicates that one entity has been modified, revised, or updated as a result of changes made by another entity.
  • C. constitutionalArticleAffected
    Indicates that a specific constitutional article is impacted, modified, or otherwise influenced by an action, event, or legal measure.
  • D. laterConstitutionalAct
    Indicates that one constitutional act occurs after another in time, establishing a later legal or constitutional measure relative to a prior one.
  • E. effectOfAmendments
    Indicates the causal impact or consequences that specific amendments have on something, such as a law, document, or situation.
  • F. None of above. chosen

Provenance (4 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_69a25497e2f08190a040f8c6e1842643 completed Feb. 28, 2026, 2:36 a.m.
NER Named-entity recognition batch_69a2594809288190b3d3b1283e7e0d00 completed Feb. 28, 2026, 2:56 a.m.
PD Predicate disambiguation batch_69a25670feb081908e26a2543ebe7b3a completed Feb. 28, 2026, 2:44 a.m.
PDg Predicate description generation batch_69a257e763d081908c54ad57d8d3060d completed Feb. 28, 2026, 2:50 a.m.
Created at: Feb. 28, 2026, 2:40 a.m.