Triple
T27011433
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Takashi Satō |
E680396
|
entity |
| Predicate | isUsedByProfessionalsIn |
P93839
|
FINISHED |
| Object | sports |
—
|
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: sports | Statement: [Takashi Satō, isUsedByProfessionalsIn, sports]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isUsedByProfessionalsIn Context triple: [Takashi Satō, isUsedByProfessionalsIn, sports]
-
A.
hasProfessionalApplication
chosen
Indicates that something is used or applied within a professional, occupational, or work-related context.
-
B.
isProfessionalService
Indicates that one entity provides specialized, expert services to another in a formal, professional capacity.
-
C.
isProfessionalUnit
Indicates that one entity functions as a formal or specialized professional unit in relation to another entity.
-
D.
isUsedUnder
Indicates that one entity is utilized or applied within the context, conditions, or framework defined by another entity.
-
E.
usedForProduct
Indicates that one entity serves as a tool, component, or means specifically employed in the creation, operation, or delivery of another entity considered as a product.
- 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_69eeeb53939c8190bd431f32b060f01f |
completed | April 27, 2026, 4:51 a.m. |
| NER | Named-entity recognition | batch_69f6352fdb788190b9bad30243690743 |
completed | May 2, 2026, 5:32 p.m. |
| PD | Predicate disambiguation | batch_69f631850ae08190a0ba51e4f1e4ccb3 |
completed | May 2, 2026, 5:16 p.m. |
Created at: April 27, 2026, 7:03 a.m.