Triple
T15750851
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kabushiki gaisha |
E381838
|
entity |
| Predicate | commonInSector |
P7254
|
FINISHED |
| Object | manufacturing companies in Japan |
—
|
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: manufacturing companies in Japan | Statement: [Kabushiki gaisha, commonInSector, manufacturing companies in Japan]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: commonInSector Context triple: [Kabushiki gaisha, commonInSector, manufacturing companies in Japan]
-
A.
commonIn
chosen
Indicates that something frequently occurs, appears, or is found within a specified context, group, or environment.
-
B.
ownerSector
Indicates the sector or industry category to which the owner of an entity belongs.
-
C.
isSectorSpecific
Indicates that something is tailored or restricted to a particular industry or sector rather than being generally applicable.
-
D.
sectorServed
Indicates the industry or economic sector that an entity primarily serves or targets with its activities, products, or services.
-
E.
formsSectorWithin
Indicates that one entity constitutes or defines a specific sector or sub-area within a larger domain, region, or organizational structure.
- 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_69d86d9e6b44819085d1f6a969ecb74c |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e0b4d6b5788190883746ee82c799f5 |
completed | April 16, 2026, 10:07 a.m. |
| PD | Predicate disambiguation | batch_69e0052c6208819098165d61d378d13b |
completed | April 15, 2026, 9:37 p.m. |
Created at: April 10, 2026, 4:47 a.m.