Triple
T7687946
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | All Star Cafe |
E174168
|
entity |
| Predicate | entertainmentFeatures |
P19394
|
FINISHED |
| Object | televised sports events |
—
|
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: televised sports events | Statement: [All Star Cafe, entertainmentFeatures, televised sports events]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: entertainmentFeatures Context triple: [All Star Cafe, entertainmentFeatures, televised sports events]
-
A.
entertainmentType
Indicates the kind or category of entertainment associated with an entity or event.
-
B.
genreFeatures
Indicates that a particular genre is characterized or defined by certain features or attributes.
-
C.
specialFeature
chosen
Indicates that an entity possesses a distinctive or noteworthy attribute, capability, or characteristic that sets it apart from others.
-
D.
featuredIn
Indicates that one entity appears or is prominently included within another entity, such as a person, work, or item being showcased in a larger work, event, or context.
-
E.
shows
Indicates that one entity presents, displays, or makes another entity visible or known to an audience or observer.
- 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_69c6995840408190a19de6c51090f46f |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c706d1f0208190bc5b695aa5736244 |
completed | March 27, 2026, 10:38 p.m. |
| PD | Predicate disambiguation | batch_69c70163dea88190ae729df50e63dfd7 |
completed | March 27, 2026, 10:15 p.m. |
Created at: March 27, 2026, 4:02 p.m.