Triple
T31085283
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bing Crosby as Bob Wallace |
E792214
|
entity |
| Predicate | primarySettingInStory |
P190297
|
FINISHED |
| Object | Vermont inn |
—
|
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: Vermont inn | Statement: [Bing Crosby as Bob Wallace, primarySettingInStory, Vermont inn]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primarySettingInStory Context triple: [Bing Crosby as Bob Wallace, primarySettingInStory, Vermont inn]
-
A.
primarySetting
Indicates that one entity serves as the main or central location, context, or environment in which the other entity’s events or activities primarily take place.
-
B.
primarySettingOf
Indicates that a location or context serves as the main or principal setting in which an entity (such as a story, event, or activity) takes place.
-
C.
primarySettingFeature
Indicates that a particular feature is the main or defining characteristic of a setting.
-
D.
settingOfPrimaryStories
Indicates the primary location or environment in which the main stories or narratives about an entity take place.
-
E.
mainSettingOfStory
chosen
Indicates that a location or environment serves as the primary setting in which the events of a story take 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_69f224ce48348190bd0fc23f656ed683 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_6a037c876524819098545e6037d3107d |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379e5174c8190a0bdde7e381b7624 |
completed | May 12, 2026, 7:05 p.m. |
Created at: April 29, 2026, 9:02 p.m.