Triple
T18262441
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mrs. Gayheart |
E437392
|
entity |
| Predicate | settingOfLifeInFiction |
P67881
|
FINISHED |
| Object | small Midwestern town |
—
|
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: small Midwestern town | Statement: [Mrs. Gayheart, settingOfLifeInFiction, small Midwestern town]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: settingOfLifeInFiction Context triple: [Mrs. Gayheart, settingOfLifeInFiction, small Midwestern town]
-
A.
settingOfFictionalLife
chosen
Indicates that a particular place or environment serves as the primary backdrop or context in which a fictional character’s life and experiences occur.
-
B.
laterSettingOfFiction
Indicates that one fictional work is set chronologically later than another within a shared narrative or story world.
-
C.
createsInFiction
Indicates that one entity is the creator or originator of another entity within a fictional or narrative context.
-
D.
cultureInFiction
Indicates that a work of fiction features, represents, or is thematically centered on a particular culture.
-
E.
livesInFiction
Indicates that one entity exists or resides within the fictional world or narrative setting created by another entity.
- 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_69d8b913351c8190932b6a426de04b41 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4ff77882c81909774aefc57ccca3e |
completed | April 19, 2026, 4:14 p.m. |
| PD | Predicate disambiguation | batch_69e44fcdee748190bae6fb76e0cb22f3 |
completed | April 19, 2026, 3:45 a.m. |
Created at: April 10, 2026, 10:34 a.m.