Triple
T22091047
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Revisionist Westerns |
E545911
|
entity |
| Predicate | oftenSetIn |
P146936
|
FINISHED |
| Object | American frontier |
—
|
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: American frontier | Statement: [Revisionist Westerns, oftenSetIn, American frontier]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: oftenSetIn Context triple: [Revisionist Westerns, oftenSetIn, American frontier]
-
A.
oftenHave
Indicates that one entity frequently possesses, experiences, or is associated with another entity.
-
B.
oftenFrom
Indicates that something frequently originates, derives, or comes from a particular source or location.
-
C.
frequentOccasion
Indicates that a particular event, situation, or condition occurs repeatedly or commonly over time.
-
D.
oftenUse
Indicates that one entity frequently or regularly uses, employs, or utilizes another entity.
-
E.
oftenSits
Indicates that an entity frequently assumes a sitting position, either habitually or on many occasions.
- 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_69e11e36d03c8190a83a1ba802b7231b |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f128e53dfc81909858cdad8b09c5fb |
completed | April 28, 2026, 9:38 p.m. |
| PD | Predicate disambiguation | batch_69e71b20ec50819096ac196c798f8e3c |
completed | April 21, 2026, 6:37 a.m. |
| PDg | Predicate description generation | batch_69e7222d208c819098b12c13e31af629 |
completed | April 21, 2026, 7:07 a.m. |
Created at: April 16, 2026, 8:29 p.m.