Triple
T28092092
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Twin Pines Mall |
E709980
|
entity |
| Predicate | realWorldFilmingCity |
P44217
|
FINISHED |
| Object | City of Industry, California |
—
|
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: City of Industry, California | Statement: [Twin Pines Mall, realWorldFilmingCity, City of Industry, California]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: realWorldFilmingCity Context triple: [Twin Pines Mall, realWorldFilmingCity, City of Industry, California]
-
A.
realFilmingTownNearby
Indicates that the actual town where filming took place is located close to the referenced place or setting.
-
B.
cityOfFictionalActivity
Indicates that a fictional activity, event, or storyline takes place in the specified city.
-
C.
formerFilmingLocation
Indicates that a place was once used as a filming location for a work but is no longer used for that purpose.
-
D.
filmingLocationContext
chosen
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_69ef9b70fd108190a875953b2e50ca91 |
completed | April 27, 2026, 5:22 p.m. |
| NER | Named-entity recognition | batch_69f6406afe448190ad9c61220d2573b4 |
completed | May 2, 2026, 6:20 p.m. |
| PD | Predicate disambiguation | batch_69f63c6a8474819091b8c6fe98e3862d |
completed | May 2, 2026, 6:03 p.m. |
Created at: April 27, 2026, 8:59 p.m.