Triple
T23381094
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Long Branch Saloon |
E593746
|
entity |
| Predicate | appearsAsSettingIn |
P15599
|
FINISHED |
| Object | fictional Western stories |
—
|
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: fictional Western stories | Statement: [Long Branch Saloon, appearsAsSettingIn, fictional Western stories]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: appearsAsSettingIn Context triple: [Long Branch Saloon, appearsAsSettingIn, fictional Western stories]
-
A.
usedAsSettingFor
chosen
Indicates that one entity serves as the backdrop, location, or environment in which another entity (such as an event, story, or activity) takes place.
-
B.
knownAsSettingFor
Indicates that something is recognized or regarded as the typical or notable setting or backdrop for something else.
-
C.
worksInSetting
Indicates that an entity performs its activities or functions within a specified environment, context, or setting.
-
D.
indicatedSetting
Indicates that one entity specifies, denotes, or points out a particular setting or configuration associated with another entity.
-
E.
coversSetting
Indicates that one entity includes or addresses a particular setting or context within its scope.
- 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_69e25d268a50819095f2fd479da8ef3f |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1a3b7eff48190be126df2211b4c85 |
completed | April 29, 2026, 6:22 a.m. |
| PD | Predicate disambiguation | batch_69f061dde2e481908308952f9c0d3c2e |
completed | April 28, 2026, 7:29 a.m. |
Created at: April 17, 2026, 5:34 p.m.