Triple
T1364405
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tales of a Wayside Inn |
E29169
|
entity |
| Predicate | frameSetting |
P1957
|
FINISHED |
| Object | a New England 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: a New England inn | Statement: [Tales of a Wayside Inn, frameSetting, a New England inn]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: frameSetting Context triple: [Tales of a Wayside Inn, frameSetting, a New England inn]
-
A.
frameType
Indicates the specific structural or categorical kind of frame associated with an entity or relation.
-
B.
frameworkPresented
Indicates that a particular framework has been formally introduced or shown to an audience or recipient.
-
C.
narrativeFrame
Indicates the overarching narrative context or perspective within which events, actions, or relationships are presented or interpreted.
-
D.
setting
chosen
Indicates the place, time, or context in which an event, action, or interaction occurs.
-
E.
filmLoopConfiguration
Indicates that a film or video is set to repeat continuously according to a specified looping configuration or behavior.
- 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_69a498d77abc8190913bf57e5f51d2c4 |
completed | March 1, 2026, 7:51 p.m. |
| NER | Named-entity recognition | batch_69a4c2b5d05c81908b49e282648e073a |
completed | March 1, 2026, 10:50 p.m. |
| PD | Predicate disambiguation | batch_69a4bef945c08190a027472fdd695ea5 |
completed | March 1, 2026, 10:34 p.m. |
Created at: March 1, 2026, 7:57 p.m.