Triple
T21659956
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Miriam Deering |
E534567
|
entity |
| Predicate | storySettingType |
P55822
|
FINISHED |
| Object | Southern Gothic mansion |
—
|
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: Southern Gothic mansion | Statement: [Miriam Deering, storySettingType, Southern Gothic mansion]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: storySettingType Context triple: [Miriam Deering, storySettingType, Southern Gothic mansion]
-
A.
storySettingEvent
Indicates that an event takes place within, or helps define, the setting or background context of a story.
-
B.
storySettingPhaseOfLife
Indicates the phase of life (e.g., childhood, adolescence, adulthood) during which the story is set or primarily takes place.
-
C.
settingOfAdventure
Indicates that a location or environment serves as the primary setting where an adventure takes place.
-
D.
fictionalStreetSetting
Indicates that an entity is set on or associated with a street that exists only within a fictional or imaginary context.
-
E.
narrativeLocationType
chosen
Indicates the type or role of a location within the structure or context of a narrative (e.g., setting, origin, destination).
- 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_69e0c467e1f48190af2650b19175abc4 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ef6c06844c81909b9c91e02fa4e6e1 |
completed | April 27, 2026, 2 p.m. |
| PD | Predicate disambiguation | batch_69e696826c3c81909270791e79760937 |
completed | April 20, 2026, 9:11 p.m. |
Created at: April 16, 2026, 6:36 p.m.