Triple
T32310335
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Civic TV Channel 83 |
E825480
|
entity |
| Predicate | productionLocationForFilm |
P4373
|
FINISHED |
| Object | Toronto |
—
|
NE NERFINISHED |
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: Toronto | Statement: [Civic TV Channel 83, productionLocationForFilm, Toronto]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: productionLocationForFilm Context triple: [Civic TV Channel 83, productionLocationForFilm, Toronto]
-
A.
filmLocationFor
chosen
Indicates a relationship where a specific place serves as the filming location for a particular film or production.
-
B.
productionCompanyLocation
Indicates the relationship between a production company and the geographic location where it is based or operates.
-
C.
filmingLocationForAdaptation
Indicates the place where an adaptation (such as a film or TV version of a work) was shot or recorded.
-
D.
filmingLocationContext
Indicates the contextual relationship specifying where the filming of an event, scene, or production took place.
-
E.
countryOfFilming
Indicates the country where the filming or production of a work physically took place.
- 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_69f3491213b88190a57094d8697a7455 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69fdbaa226708190b8ed96e93aad38de |
completed | May 8, 2026, 10:27 a.m. |
| PD | Predicate disambiguation | batch_69fdb58b07e48190837e00966de050d4 |
completed | May 8, 2026, 10:06 a.m. |
Created at: May 1, 2026, 12:46 a.m.