Triple
T29090747
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Koji Kobayashi |
E734844
|
entity |
| Predicate | hasDomainOfInfluence |
P148038
|
FINISHED |
| Object | Japanese electronics sector |
—
|
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 electronics sector | Statement: [Koji Kobayashi, hasDomainOfInfluence, Japanese electronics sector]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDomainOfInfluence Context triple: [Koji Kobayashi, hasDomainOfInfluence, Japanese electronics sector]
-
A.
domainOfInfluence
chosen
Indicates the scope or area over which an entity has power, control, or significant effect.
-
B.
indicatesDomain
Indicates a domain or area of knowledge, activity, or applicability to which something (such as a concept, resource, or entity) belongs or is relevant.
-
C.
containsDomain
Indicates that one entity includes or encompasses a specific domain as part of its scope, structure, or area of applicability.
-
D.
affectedDomain
Indicates the domain, field, or area that is impacted or influenced by a given action, event, or condition.
-
E.
assessesDomain
Indicates that one entity evaluates or judges the scope, area, or field of 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_69f05b0ed66481908f2e864fa550d2f1 |
completed | April 28, 2026, 7 a.m. |
| NER | Named-entity recognition | batch_69f69edbb7648190bd89c57e0932eac1 |
completed | May 3, 2026, 1:03 a.m. |
| PD | Predicate disambiguation | batch_69f69d17e8d48190b30bcc2f4bd81eb2 |
completed | May 3, 2026, 12:55 a.m. |
Created at: April 28, 2026, 11:04 a.m.