Triple
T37402617
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hollywood Bowl |
E929039
|
entity |
| Predicate | typicalVenueFeature |
P124384
|
FINISHED |
| Object | multiple bowling lanes |
—
|
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: multiple bowling lanes | Statement: [Hollywood Bowl, typicalVenueFeature, multiple bowling lanes]
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 (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_69f76ebbf79c8190b85bbcf3a6be57e4 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_6a037c8efcd4819088c2aeead65d93df |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a13a1308190a202df66f4781855 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:16 p.m.