Triple
T15409280
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Checkers franchises |
E368541
|
entity |
| Predicate | operatingFormat |
P38824
|
FINISHED |
| Object | freestanding restaurant units |
—
|
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: freestanding restaurant units | Statement: [Checkers franchises, operatingFormat, freestanding restaurant units]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: operatingFormat Context triple: [Checkers franchises, operatingFormat, freestanding restaurant units]
-
A.
operatesInFormat
chosen
Indicates that an entity functions, performs its role, or is carried out using a specified format.
-
B.
presentedInFormat
Indicates that something is expressed, delivered, or made available using a particular format or representation.
-
C.
featuresFormat
Indicates that something (such as a product, service, or medium) is presented, delivered, or made available in a particular format or configuration.
-
D.
operationalForm
Indicates that one entity is the specific operational or executable form of another, more abstract entity.
-
E.
formatCompatibleWith
Indicates that one format can be correctly used, interpreted, or processed in conjunction with another format without conflict or loss of information.
- 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_69d85a16c68c819099c1b547fbc87b32 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03ea4f13c819085d26fd32b5dca6f |
completed | April 16, 2026, 1:43 a.m. |
| PD | Predicate disambiguation | batch_69ded27b8cac8190bfa77698d53c5d1c |
completed | April 14, 2026, 11:49 p.m. |
Created at: April 10, 2026, 3:20 a.m.