Triple
T186385
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | kishida230 |
E3989
|
entity |
| Predicate | topicOfPosts |
P380
|
FINISHED |
| Object | Japanese domestic policy |
—
|
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: Japanese domestic policy | Statement: [kishida230, topicOfPosts, Japanese domestic policy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: topicOfPosts Context triple: [kishida230, topicOfPosts, Japanese domestic policy]
-
A.
topicOfAdvice
Indicates that one entity is the subject or focus about which advice is being given by another entity.
-
B.
subjectMatter
Indicates the topic, theme, or content area that something (such as a work, document, or discussion) is about.
-
C.
theme
Indicates the entity that is the primary participant or content affected or characterized by an action, event, or state.
-
D.
category
Indicates that one entity is classified as a member or type within the grouping or class defined by another entity.
-
E.
isAbout
chosen
Indicates that one entity has as its subject, focus, or primary concern the content, topic, or theme represented by another entity.
- 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_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. |
Created at: Feb. 28, 2026, 2:40 a.m.