Triple
T5140285
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Television City, Hollywood |
E115928
|
entity |
| Predicate | numberOfStudios |
P61779
|
FINISHED |
| Object | multiple soundstages |
—
|
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 soundstages | Statement: [Television City, Hollywood, numberOfStudios, multiple soundstages]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfStudios Context triple: [Television City, Hollywood, numberOfStudios, multiple soundstages]
-
A.
hasStudio
Indicates that an entity (such as a film, game, or production) is associated with or produced by a particular studio.
-
B.
filmNumberInStudioCanon
Indicates the ordinal position a film holds within a studio’s official canon or main sequence of releases.
-
C.
majorStudio
Indicates that an entity is a large, primary film or media production and distribution company within the entertainment industry.
-
D.
hasRecordingStudio
Indicates that an entity possesses, operates, or is associated with a recording studio.
-
E.
filmStudioLot
Indicates a relationship where a film studio owns, operates, or is associated with a specific studio lot or production facility.
- 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_69bd44459a988190a772a5c2ec6a1965 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd78d7f4d081908d59adcd86f52f1d |
completed | March 20, 2026, 4:42 p.m. |
| PD | Predicate disambiguation | batch_69bd77ae2f10819098bb8939106e1281 |
completed | March 20, 2026, 4:37 p.m. |
| PDg | Predicate description generation | batch_69bd78d6a1388190804dcf568ca92129 |
completed | March 20, 2026, 4:41 p.m. |
Created at: March 20, 2026, 1:43 p.m.