Triple
T51653
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Constitution of Japan |
E1013
|
entity |
| Predicate | containsArticle |
P2947
|
FINISHED |
| Object | Article 1 |
—
|
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: Article 1 | Statement: [Constitution of Japan, containsArticle, Article 1]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: containsArticle Context triple: [Constitution of Japan, containsArticle, Article 1]
-
A.
articleCount
Indicates the number of articles associated with a given entity or context.
-
B.
keyArticle
Indicates that an article is a primary or central reference for understanding, supporting, or defining another entity or topic.
-
C.
Article5Meaning
Indicates that a legal or policy document specifies the meaning, scope, or implications of its Article 5 provision.
-
D.
hasPublication
Indicates that an entity is associated with or responsible for a specific publication.
-
E.
publishedIn
Indicates that a work (such as an article, paper, or book) has been formally released or made available within a specific venue, medium, or publication.
- 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_69a2480baefc81909951b14058479aa2 |
completed | Feb. 28, 2026, 1:42 a.m. |
| NER | Named-entity recognition | batch_69a24ba7016481909d595402712db6e2 |
completed | Feb. 28, 2026, 1:57 a.m. |
| PD | Predicate disambiguation | batch_69a24ac23f04819080cef9365ed990d4 |
completed | Feb. 28, 2026, 1:54 a.m. |
| PDg | Predicate description generation | batch_69a24ba5da048190a484963cb5a9bb2b |
completed | Feb. 28, 2026, 1:57 a.m. |
Created at: Feb. 28, 2026, 1:47 a.m.