Triple
T19691932
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kettle Brand Air Fried potato chips |
E472854
|
entity |
| Predicate | typicalLocationSold |
P15059
|
FINISHED |
| Object | grocery stores |
—
|
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: grocery stores | Statement: [Kettle Brand Air Fried potato chips, typicalLocationSold, grocery stores]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalLocationSold Context triple: [Kettle Brand Air Fried potato chips, typicalLocationSold, grocery stores]
-
A.
soldAt
chosen
Indicates that a product or item is offered for sale at a particular location, venue, or outlet.
-
B.
oftenLocatedAt
Indicates that an entity is frequently or commonly found at, or associated with being in, a particular location.
-
C.
auctionLocation
Indicates the place or venue where an auction is held or takes place.
-
D.
secondaryRegionSold
Indicates that an item or service was sold in a secondary (non-primary) geographic region or market.
-
E.
typicalUseLocation
Indicates the usual or most common location where an entity is used or operates.
- 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_69d8e515bef88190bc30781aea50537a |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e64210cddc8190836faa2996a44457 |
completed | April 20, 2026, 3:11 p.m. |
| PD | Predicate disambiguation | batch_69e53039ea808190a9106a53f564ab92 |
completed | April 19, 2026, 7:42 p.m. |
Created at: April 10, 2026, 1:46 p.m.