Triple
T3204031
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | World Series television broadcasts |
E67117
|
entity |
| Predicate | typicalCameraSetup |
P43677
|
FINISHED |
| Object | multiple-camera production |
—
|
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-camera production | Statement: [World Series television broadcasts, typicalCameraSetup, multiple-camera production]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalCameraSetup Context triple: [World Series television broadcasts, typicalCameraSetup, multiple-camera production]
-
A.
typicalSetup
Indicates that an entity is arranged, configured, or organized in its standard or commonly used setup relative to another entity or context.
-
B.
cameraConfiguration
chosen
Indicates the specific setup or arrangement of a camera’s parameters or components in a given context.
-
C.
meetsInCamera
Indicates that two or more entities are physically present together in the same camera frame or shot at the same time.
-
D.
cameraStyle
Indicates the characteristic visual approach or technique used by a camera in capturing or presenting imagery.
-
E.
hasCamera
Indicates that an entity is equipped with or possesses a camera.
- 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_69ad8589bd988190afa7ed2bdffb7b33 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69adaa54124c8190a22089ce2eaedab5 |
completed | March 8, 2026, 4:56 p.m. |
| PD | Predicate disambiguation | batch_69ad9e078f7c8190813d9fcb4f5071fb |
completed | March 8, 2026, 4:04 p.m. |
Created at: March 8, 2026, 3:07 p.m.