Triple
T30785682
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | メタボリズム |
E783948
|
entity |
| Predicate | 影響を受けた分野 |
P19800
|
FINISHED |
| Object | 都市計画 |
—
|
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: 都市計画 | Statement: [メタボリズム, 影響を受けた分野, 都市計画]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 影響を受けた分野 Context triple: [メタボリズム, 影響を受けた分野, 都市計画]
-
A.
hasImpactArea
Indicates that an entity affects, influences, or has consequences within a specific area, domain, or scope.
-
B.
influencedAspectOf
Indicates that one entity has affected, shaped, or altered a particular aspect or component of another entity.
-
C.
influenced
Indicates that one entity has affected, shaped, or altered another entity’s state, behavior, or characteristics.
-
D.
influencedPolicyArea
Indicates that one entity has affected, shaped, or guided the development, direction, or implementation of a particular policy area associated with another entity.
-
E.
hasInfluenceOnDiscipline
chosen
Indicates that one entity exerts an effect, shaping force, or contributing impact on the development, direction, or state of a particular discipline.
- 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_69f224b213c8819083886073f90b647e |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f68fe8168c8190b083be0e33988b9c |
completed | May 2, 2026, 11:59 p.m. |
| PD | Predicate disambiguation | batch_69f686140aa08190a35f62572b2db9b6 |
completed | May 2, 2026, 11:17 p.m. |
Created at: April 29, 2026, 8:41 p.m.