Triple
T29582106
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jack Torrance about the hotel’s history |
E753615
|
entity |
| Predicate | relatesToSetting |
P44691
|
FINISHED |
| Object | isolatedMountainHotel |
—
|
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: isolatedMountainHotel | Statement: [Jack Torrance about the hotel’s history, relatesToSetting, isolatedMountainHotel]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relatesToSetting Context triple: [Jack Torrance about the hotel’s history, relatesToSetting, isolatedMountainHotel]
-
A.
associatedWithSetting
chosen
Indicates that one entity is connected or linked to a particular context, environment, or setting in which it occurs or is relevant.
-
B.
coversSetting
Indicates that one entity includes or addresses a particular setting or context within its scope.
-
C.
indicatedSetting
Indicates that one entity specifies, denotes, or points out a particular setting or configuration associated with another entity.
-
D.
knownAsSettingFor
Indicates that something is recognized or regarded as the typical or notable setting or backdrop for something else.
-
E.
usedAsSettingFor
Indicates that one entity serves as the backdrop, location, or environment in which another entity (such as an event, story, or activity) 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_69f0ef80bf8c8190ad286e99f7df0c63 |
completed | April 28, 2026, 5:33 p.m. |
| NER | Named-entity recognition | batch_6a0174142430819084aa1235500b9d3b |
completed | May 11, 2026, 6:15 a.m. |
| PD | Predicate disambiguation | batch_6a0171a6e0088190958679bb6cb24a70 |
completed | May 11, 2026, 6:05 a.m. |
Created at: April 28, 2026, 6:07 p.m.