Triple
T13814152
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Studio 1A |
E331970
|
entity |
| Predicate | hasLiveCrowdOutside |
P111588
|
FINISHED |
| Object | frequently |
—
|
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: frequently | Statement: [Studio 1A, hasLiveCrowdOutside, frequently]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLiveCrowdOutside Context triple: [Studio 1A, hasLiveCrowdOutside, frequently]
-
A.
hasCrowdLevel
Indicates the degree or intensity of how crowded a place, event, or situation is.
-
B.
hasEventDayCrowdManagement
Indicates that specific crowd management measures or responsibilities are associated with the day on which an event takes place.
-
C.
crowdWas
Indicates that a crowd possessed or exhibited a particular state, quality, or condition.
-
D.
hasLiveAudienceCapability
Indicates that an entity is capable of supporting or engaging with a live, in-person audience.
-
E.
hasAudienceSize
Indicates the relationship between an entity and the number of people or size of group that receives, views, or engages with it.
- 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_69d81c59f8808190a851bc56afdc55e9 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de027198f8819095da3e714ac241f5 |
completed | April 14, 2026, 9:01 a.m. |
| PD | Predicate disambiguation | batch_69dbc862e9608190bd8a3d883959b7e4 |
completed | April 12, 2026, 4:29 p.m. |
| PDg | Predicate description generation | batch_69dcad0eea9881908f71e1eed9a2446b |
completed | April 13, 2026, 8:45 a.m. |
Created at: April 9, 2026, 10:12 p.m.