Triple
T1305073
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | BBC facilities at MediaCityUK |
E27855
|
entity |
| Predicate | hasStudioType |
P2836
|
FINISHED |
| Object | high-definition television studios |
—
|
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: high-definition television studios | Statement: [BBC facilities at MediaCityUK, hasStudioType, high-definition television studios]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStudioType Context triple: [BBC facilities at MediaCityUK, hasStudioType, high-definition television studios]
-
A.
hasMainStudioShow
Indicates that an entity serves as the primary studio-based show associated with another entity (such as a network, channel, or program brand).
-
B.
hasOfficeType
Indicates that an entity’s office is classified as a specific type or category of office.
-
C.
hasFacilityType
chosen
Indicates that an entity possesses or is associated with a specific type or category of facility.
-
D.
hasBenchType
Indicates that an entity is associated with or characterized by a specific type or category of bench.
-
E.
hasSculptor
Indicates that one entity serves as the sculptor (creator of a sculpture) of another entity.
- 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_69a496d7d83481908f83085854e51328 |
completed | March 1, 2026, 7:43 p.m. |
| NER | Named-entity recognition | batch_69a4c13393388190b784d6bd8c447dda |
completed | March 1, 2026, 10:44 p.m. |
| PD | Predicate disambiguation | batch_69a4bee8544c8190874efd9bae9bccf9 |
completed | March 1, 2026, 10:34 p.m. |
Created at: March 1, 2026, 7:51 p.m.