Triple
T25214975
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Water (2005 film) |
E631803
|
entity |
| Predicate | originallyPlannedFilmingLocation |
P175605
|
FINISHED |
| Object | Varanasi |
—
|
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: Varanasi | Statement: [Water (2005 film), originallyPlannedFilmingLocation, Varanasi]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: originallyPlannedFilmingLocation Context triple: [Water (2005 film), originallyPlannedFilmingLocation, Varanasi]
-
A.
formerFilmingLocation
Indicates that a place was once used as a filming location for a work but is no longer used for that purpose.
-
B.
filmingLocationForAdaptation
Indicates the place where an adaptation (such as a film or TV version of a work) was shot or recorded.
-
C.
countryOfFilming
Indicates the country where the filming or production of a work physically took place.
-
D.
filmingLocationContext
Indicates the contextual relationship specifying where the filming of an event, scene, or production took place.
-
E.
placeOfShooting
Indicates the location where a shooting event took 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_69e75a8d1aa48190a4320acd3654762c |
completed | April 21, 2026, 11:07 a.m. |
| NER | Named-entity recognition | batch_69f6d74b20a48190900dda1014cc13a8 |
completed | May 3, 2026, 5:04 a.m. |
| PD | Predicate disambiguation | batch_69f6d26ceb08819091c71c001e954936 |
completed | May 3, 2026, 4:43 a.m. |
| PDg | Predicate description generation | batch_69f6d6a482fc8190b526291cd99b8696 |
completed | May 3, 2026, 5:01 a.m. |
Created at: April 21, 2026, 12:58 p.m.