Triple
T37402617
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hollywood Bowl |
E929039
|
entity |
| Predicate | typicalVenueFeature |
—
|
GENERATED |
| Object | multiple bowling lanes |
—
|
UNRECOGNIZED GENERATED |
How this triple was built (1 step)
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.
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalVenueFeature Context triple: [Hollywood Bowl, typicalVenueFeature, multiple bowling lanes]
-
A.
featuresVenue
Indicates that one entity includes, hosts, or is associated with a particular venue as part of its offering or context.
-
B.
typicalVenueSetting
Indicates the usual or characteristic type of venue or setting in which an event, activity, or interaction typically takes place.
-
C.
typicalAmenity
chosen
Indicates that something is a common or characteristic amenity typically associated with a given entity or context.
-
D.
cuisineFeature
Indicates a characteristic, quality, or notable aspect that describes or distinguishes a particular cuisine.
-
E.
typicalVenues
Indicates that the specified locations are common or standard places where the associated activity, event, or entity usually occurs or is hosted.
- F. None of above.
Provenance (1 batch)
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_69f76ebbf79c8190b85bbcf3a6be57e4 |
completed | May 3, 2026, 3:50 p.m. |
Created at: May 3, 2026, 4:16 p.m.