Triple
T20187079
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Verity |
E492889
|
entity |
| Predicate | employerBusinessType |
P2510
|
FINISHED |
| Object | joke shop |
—
|
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: joke shop | Statement: [Verity, employerBusinessType, joke shop]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: employerBusinessType Context triple: [Verity, employerBusinessType, joke shop]
-
A.
employerType
chosen
Indicates the classification or category of an employer in relation to the entity (e.g., public, private, nonprofit, self-employed).
-
B.
issuerBusinessType
Indicates the category or nature of business activity that the issuing entity is engaged in.
-
C.
hasTypeOfBusinesses
Indicates that an entity is associated with or contains specific categories or kinds of businesses.
-
D.
eligibleBusinessType
Indicates that a business entity qualifies under specified criteria to be considered an eligible type for a particular program, rule, or context.
-
E.
stateOfBusiness
Indicates the current operational or financial condition or status of a business at a given point in time.
- 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_69da6268a034819081cbd9ea5a1c9475 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e66ad143c48190b9d52c331e8101d6 |
completed | April 20, 2026, 6:05 p.m. |
| PD | Predicate disambiguation | batch_69e55b11124c8190babacf2a0fe2d057 |
completed | April 19, 2026, 10:45 p.m. |
Created at: April 11, 2026, 11:36 p.m.