Triple
T11293295
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Macca’s |
E267383
|
entity |
| Predicate | refersToProductCategory |
P39625
|
FINISHED |
| Object | fast food |
—
|
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: fast food | Statement: [Macca’s, refersToProductCategory, fast food]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: refersToProductCategory Context triple: [Macca’s, refersToProductCategory, fast food]
-
A.
appliesToProductType
Indicates that something (such as a rule, offer, or condition) is relevant or applicable specifically to a certain type or category of product.
-
B.
apparentCategory
Indicates the category or type that something seems to belong to based on its observable characteristics, regardless of its true or underlying classification.
-
C.
associatedBrandCategory
chosen
Indicates that a brand is linked to or classified under a particular product or service category.
-
D.
categoryIUsedFor
Indicates that one entity is used as a category or classification label for another entity.
-
E.
byProduct
Indicates that one entity is produced incidentally or as a secondary result of a process, activity, or creation involving another 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_69d6aac993a08190a6f36445ebaf9a43 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e98b149481909f432a6b9ef8bfbb |
completed | April 9, 2026, 6:01 p.m. |
| PD | Predicate disambiguation | batch_69d787a6ca2c8190afdc24b61ccd3f8a |
completed | April 9, 2026, 11:04 a.m. |
Created at: April 8, 2026, 9:32 p.m.