Triple
T30884127
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hooker Falls |
E786709
|
entity |
| Predicate | hasFilmingAssociation |
P196425
|
FINISHED |
| Object | DuPont State Forest filming location area |
—
|
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: DuPont State Forest filming location area | Statement: [Hooker Falls, hasFilmingAssociation, DuPont State Forest filming location area]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFilmingAssociation Context triple: [Hooker Falls, hasFilmingAssociation, DuPont State Forest filming location area]
-
A.
alsoFilmedIn
Indicates that the same film or video production was additionally shot or recorded in another specified location.
-
B.
filmedAs
Indicates that an entity was recorded or captured in a particular form, version, or role during a filming or production process.
-
C.
filmedFor
Indicates that something was recorded or produced specifically for a particular purpose, audience, platform, or project.
-
D.
filmedBefore
Indicates that one filming event occurred earlier in time than another filming event.
-
E.
stateOfFilming
Indicates the location or jurisdiction (such as a state or region) where the filming of a work takes place.
- 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_69f224bae17c8190bb3a6a28e3d019df |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69fe349879848190bcd77e3cc3470458 |
completed | May 8, 2026, 7:08 p.m. |
| PD | Predicate disambiguation | batch_69fe31e3cf908190b23ebc2f7fe58722 |
completed | May 8, 2026, 6:56 p.m. |
| PDg | Predicate description generation | batch_69fe349739cc8190a21c408208312e6c |
completed | May 8, 2026, 7:08 p.m. |
Created at: April 29, 2026, 8:48 p.m.