Triple
T25289189
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jean Dry Lake |
E634031
|
entity |
| Predicate | filmingAttraction |
P31730
|
FINISHED |
| Object | featureless landscape |
—
|
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: featureless landscape | Statement: [Jean Dry Lake, filmingAttraction, featureless landscape]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: filmingAttraction Context triple: [Jean Dry Lake, filmingAttraction, featureless landscape]
-
A.
filmingStudio
Indicates that a studio is responsible for producing or filming a particular audiovisual work.
-
B.
notableFilmingLocation
chosen
Indicates that a place served as a significant or well-known location where a film or television production was shot.
-
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
Indicates the contextual relationship specifying where the filming of an event, scene, or production took place.
-
E.
filmingLocationPattern
Indicates the typical or recurring geographic pattern of locations where filming for a production takes 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_69e75a9503d48190b80a005c6af0cb50 |
completed | April 21, 2026, 11:08 a.m. |
| NER | Named-entity recognition | batch_69f48e0c2aa88190aca9e47be7138854 |
completed | May 1, 2026, 11:27 a.m. |
| PD | Predicate disambiguation | batch_69f4806d93dc8190b9dff4c63186faff |
completed | May 1, 2026, 10:29 a.m. |
Created at: April 21, 2026, 1:21 p.m.