Triple
T36135920
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Chicken Roaster |
E1045165
|
entity |
| Predicate | featuresFictionalRestaurant |
P120578
|
FINISHED |
| Object | Kenny Rogers Roasters |
E17634
|
NE 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: Kenny Rogers Roasters | Statement: [The Chicken Roaster, featuresFictionalRestaurant, Kenny Rogers Roasters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresFictionalRestaurant Context triple: [The Chicken Roaster, featuresFictionalRestaurant, Kenny Rogers Roasters]
-
A.
restaurantContained
Indicates that a restaurant is physically located within or is a part of a larger place or establishment.
-
B.
featuresVenue
Indicates that one entity includes, hosts, or is associated with a particular venue as part of its offering or context.
-
C.
hasFictionalDiner
chosen
Indicates that one entity features or includes a fictional diner associated with another entity.
-
D.
restaurantDesignedBy
Indicates that a restaurant was created or planned by a particular designer or architect.
-
E.
restaurantName
Indicates the name assigned to a restaurant as its identifying label.
- F. None of above.
Provenance (4 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_69f76e36a4508190b5bfc8f594272a4c |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_6a037c8d06cc8190ab6a5e18d9d2571e |
completed | May 12, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a38de19a1b08190835bd77e239fef33 |
completed | June 22, 2026, 7:02 a.m. |
| PD | Predicate disambiguation | batch_6a037a0895b48190acdd88dc10db7be7 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:08 p.m.