Triple
T31509647
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tabernas Desert |
E803906
|
entity |
| Predicate | notableFilmShotIn |
P31730
|
FINISHED |
| Object | The Good, the Bad and the Ugly |
E52284
|
NE 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: The Good, the Bad and the Ugly | Statement: [Tabernas Desert, notableFilmShotIn, The Good, the Bad and the Ugly]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableFilmShotIn Context triple: [Tabernas Desert, notableFilmShotIn, The Good, the Bad and the Ugly]
-
A.
notableFilmingLocation
chosen
Indicates that a place served as a significant or well-known location where a film or television production was shot.
-
B.
cinematographyNotedFor
Indicates that the subject’s cinematography is especially recognized or distinguished for the object (such as a particular work, style, or notable quality).
-
C.
notableScene
Indicates that a particular scene is especially significant, memorable, or noteworthy within a work or context.
-
D.
shotIn
Indicates that an event, scene, or media production was filmed or recorded at a particular location.
-
E.
placeOfShooting
Indicates the location where a shooting event took place.
- F. None of above.
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_69f348ceb0a48190ae7feca263b6296c |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_6a037c876524819098545e6037d3107d |
completed | May 12, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a2b1475023c81908f5e12860203a93e |
completed | June 11, 2026, 8:03 p.m. |
| PD | Predicate disambiguation | batch_6a0379e7aa0c8190bdc9ee4d54fc821b |
completed | May 12, 2026, 7:05 p.m. |
Created at: April 30, 2026, 9:49 p.m.