Triple
T29264583
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Celebrity Big Brother (UK) 2018 |
E741941
|
entity |
| Predicate | hasCameraCoverage |
P194007
|
FINISHED |
| Object | 24-hour recording |
—
|
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: 24-hour recording | Statement: [Celebrity Big Brother (UK) 2018, hasCameraCoverage, 24-hour recording]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCameraCoverage Context triple: [Celebrity Big Brother (UK) 2018, hasCameraCoverage, 24-hour recording]
-
A.
sensorCoverage
Indicates that a sensor’s detection or monitoring area spatially covers or includes a given region, object, or point.
-
B.
hasCamera
Indicates that an entity is equipped with or possesses a camera.
-
C.
viewfinderCoverage
Indicates the extent to which what is seen through a camera’s viewfinder matches the actual area captured in the final image.
-
D.
hasCCTV
Indicates that one entity is equipped with or monitored by a CCTV (closed-circuit television) system installed or provided by another entity.
-
E.
hasAreaOfCoverage
Indicates that an entity provides services, influence, or applicability within a specified geographic or conceptual region.
- 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_69f0912065c08190bddd23e20e8ef18e |
completed | April 28, 2026, 10:51 a.m. |
| NER | Named-entity recognition | batch_69fd5d48855c8190bd93070b6a00d8b5 |
completed | May 8, 2026, 3:49 a.m. |
| PD | Predicate disambiguation | batch_69fd5c9aabb88190912800d90184a89d |
completed | May 8, 2026, 3:46 a.m. |
| PDg | Predicate description generation | batch_69fd5d47da488190a4f2dbd44a0a83b2 |
completed | May 8, 2026, 3:49 a.m. |
Created at: April 28, 2026, 12:43 p.m.