Triple
T29967870
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 川上哲治 |
E761237
|
entity |
| Predicate | プロ入り |
P150010
|
FINISHED |
| Object | 1938年 |
—
|
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: 1938年 | Statement: [川上哲治, プロ入り, 1938年]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: プロ入り Context triple: [川上哲治, プロ入り, 1938年]
-
A.
playedProfessionalFrom
chosen
Indicates that an individual played professional-level sports for a particular team or organization starting from a specified time.
-
B.
isPro
Indicates that an entity is a professional or expert in a particular field, activity, or domain.
-
C.
isAmateurOrProfessional
Indicates that an entity participates in an activity either at an amateur level or a professional level.
-
D.
semiProfessionalTiers
Indicates a relationship in which entities are organized or classified into tiers that represent semi-professional levels or statuses.
-
E.
wasAmateurOrSemiPro
Indicates that the subject participated in an activity at an amateur or semi-professional level, rather than as a full professional.
- 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_69f22467626081908d5afea489590e96 |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69f6786bd7208190b8bb4aa26506f597 |
completed | May 2, 2026, 10:19 p.m. |
| PD | Predicate disambiguation | batch_69f66ec8298c8190b41fe9d182c05676 |
completed | May 2, 2026, 9:38 p.m. |
Created at: April 29, 2026, 6:30 p.m.