Triple
T16323920
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Moe Szyslak |
E396365
|
entity |
| Predicate | runsBusinessType |
P68868
|
FINISHED |
| Object | tavern |
—
|
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: tavern | Statement: [Moe Szyslak, runsBusinessType, tavern]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: runsBusinessType Context triple: [Moe Szyslak, runsBusinessType, tavern]
-
A.
hasTypeOfBusinesses
chosen
Indicates that an entity is associated with or contains specific categories or kinds of businesses.
-
B.
hasBusinessTypeAlong
Indicates that a business or commercial entity located along a route, corridor, or area is associated with a specific type or category of business activity.
-
C.
eligibleBusinessType
Indicates that a business entity qualifies under specified criteria to be considered an eligible type for a particular program, rule, or context.
-
D.
stateOfBusiness
Indicates the current operational or financial condition or status of a business at a given point in time.
-
E.
hasBusiness
Indicates that one entity owns, operates, or is formally associated with a business entity.
- 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_69d87f255b788190a400eba031dd85d8 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e296b8fe988190adee72b23246052f |
completed | April 17, 2026, 8:23 p.m. |
| PD | Predicate disambiguation | batch_69e219fc72c881909d452274e7af8238 |
completed | April 17, 2026, 11:31 a.m. |
Created at: April 10, 2026, 5:06 a.m.