Triple
T26142804
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Toshiaki |
E659566
|
entity |
| Predicate | nameBearersInclude |
P116510
|
FINISHED |
| Object | multiple Japanese individuals across different fields |
—
|
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: multiple Japanese individuals across different fields | Statement: [Toshiaki, nameBearersInclude, multiple Japanese individuals across different fields]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nameBearersInclude Context triple: [Toshiaki, nameBearersInclude, multiple Japanese individuals across different fields]
-
A.
typicalNameBearers
chosen
Indicates that the subject is a common or characteristic name borne by the entities in the object set.
-
B.
nameBearerType
Indicates the specific role or capacity in which an entity bears or carries a given name (e.g., as a person, place, organization, or other type of name bearer).
-
C.
hasSurnameBearer
Indicates that a particular surname is borne or carried by a specific person or entity.
-
D.
nameBearersUsuallyHaveLegalName
Indicates that entities which bear a certain name typically also possess that name as their official legal name.
-
E.
raceOfBearers
Indicates the racial or ethnic group to which the bearers (individuals or entities) belong.
- 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_69ee5bc496a88190af7deb7ab5e081de |
completed | April 26, 2026, 6:39 p.m. |
| NER | Named-entity recognition | batch_69f60be63218819089ef0c5eb968db2f |
completed | May 2, 2026, 2:36 p.m. |
| PD | Predicate disambiguation | batch_69f5b0021da88190bdd4cf2698c23edf |
completed | May 2, 2026, 8:04 a.m. |
Created at: April 26, 2026, 8:21 p.m.