Triple
T1518800
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ESPN Wide World of Sports Grill |
E32178
|
entity |
| Predicate | entertainmentType |
P30079
|
FINISHED |
| Object | live sports viewing |
—
|
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: live sports viewing | Statement: [ESPN Wide World of Sports Grill, entertainmentType, live sports viewing]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: entertainmentType Context triple: [ESPN Wide World of Sports Grill, entertainmentType, live sports viewing]
-
A.
notableProgramType
Indicates that the subject is recognized for or associated with a particular type or category of program.
-
B.
genreOfAppearance
Indicates the genre or type of creative work in which an entity appears.
-
C.
theaterType
Indicates the specific kind or category of theater associated with an entity (e.g., cinema, opera house, drama theater).
-
D.
theatreType
Indicates the specific category or kind of theatre associated with an entity, such as its format, style, or operational model.
-
E.
filmType
Indicates the specific category or genre that a film belongs to.
- F. None of above. chosen
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_69a885e8caf88190a5fbb6159ce87786 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a93d4756888190bf3872154de11539 |
completed | March 5, 2026, 8:22 a.m. |
| PD | Predicate disambiguation | batch_69a907ac7ea081908dd95bb5cc3b9847 |
completed | March 5, 2026, 4:33 a.m. |
| PDg | Predicate description generation | batch_69a93d462f208190b27ef5cd631bce12 |
completed | March 5, 2026, 8:22 a.m. |
Created at: March 4, 2026, 7:26 p.m.