Triple
T12874503
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ray Kroc |
E307929
|
entity |
| Predicate | openedRestaurant |
P43960
|
FINISHED |
| Object | McDonald's restaurant in Des Plaines, Illinois, in 1955 |
—
|
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: McDonald's restaurant in Des Plaines, Illinois, in 1955 | Statement: [Ray Kroc, openedRestaurant, McDonald's restaurant in Des Plaines, Illinois, in 1955]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: openedRestaurant Context triple: [Ray Kroc, openedRestaurant, McDonald's restaurant in Des Plaines, Illinois, in 1955]
-
A.
EncounterRestaurantOpening
Indicates a situation where an entity comes across or experiences the opening or start of operations of a restaurant.
-
B.
openingTime
chosen
Indicates the time at which a place, service, or event begins operating or becomes accessible.
-
C.
EncounterRestaurantClosure
Indicates that an entity experiences or comes across the situation of a restaurant being closed.
-
D.
homeVenueOpened
Indicates that a venue has officially begun operating as the designated home location for a particular team or organization.
-
E.
hasRestaurant
Indicates that one entity possesses, operates, or contains a restaurant associated with it.
- 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_69d7bdf69bc48190af6c2621f28ca351 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d97c7f91d08190aac2f6419d3ba992 |
completed | April 10, 2026, 10:41 p.m. |
| PD | Predicate disambiguation | batch_69d96fa55b888190ab1612e93c41aec4 |
completed | April 10, 2026, 9:46 p.m. |
Created at: April 9, 2026, 5:38 p.m.