Triple
T3067435
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jeremy Irvine as young Eric Lomax |
E62136
|
entity |
| Predicate | filmingLocationContext |
P44217
|
FINISHED |
| Object | scenes set in Japanese POW camps |
—
|
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: scenes set in Japanese POW camps | Statement: [Jeremy Irvine as young Eric Lomax, filmingLocationContext, scenes set in Japanese POW camps]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: filmingLocationContext Context triple: [Jeremy Irvine as young Eric Lomax, filmingLocationContext, scenes set in Japanese POW camps]
-
A.
notableFilmingLocation
Indicates that a place served as a significant or well-known location where a film or television production was shot.
-
B.
filmLocationFor
Indicates a relationship where a specific place serves as the filming location for a particular film or production.
-
C.
countryOfFilming
Indicates the country where the filming or production of a work physically took place.
-
D.
filmingStudio
Indicates that a studio is responsible for producing or filming a particular audiovisual work.
-
E.
placeOfRecording
Indicates the location where an audio, video, or other recording was made.
- 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_69ad85793e5c8190a358049bc4a98d8c |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada0fea06881909e5251eea26599ac |
completed | March 8, 2026, 4:17 p.m. |
| PD | Predicate disambiguation | batch_69ad9624b7a0819091d255614f5819ea |
completed | March 8, 2026, 3:30 p.m. |
| PDg | Predicate description generation | batch_69ad97f7630c81908e1ca8a69611cff6 |
completed | March 8, 2026, 3:38 p.m. |
Created at: March 8, 2026, 3:02 p.m.