Triple
T35799070
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Autumnal |
E1034916
|
entity |
| Predicate | hasSinisterHometownTrope |
P195838
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [The Autumnal, hasSinisterHometownTrope, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSinisterHometownTrope Context triple: [The Autumnal, hasSinisterHometownTrope, true]
-
A.
hasFictionalNearbyTown
Indicates that an entity is associated with a fictional town located in its vicinity or surrounding area.
-
B.
hasMischievousProtagonist
Indicates that the work’s main character habitually engages in playful, naughty, or rule-breaking behavior.
-
C.
hasFictionalTownBasedOn
Indicates that a fictional town is modeled on, inspired by, or derived from a specific real-world town or location.
-
D.
homeTownInSeries
Indicates that a character’s hometown is located within a particular fictional series or narrative universe.
-
E.
hasSmallTownCharacter
Indicates that something possesses the qualities or atmosphere typically associated with a small town, such as intimacy, familiarity, and a close-knit community feel.
- F. None of above. chosen
Provenance (4 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_69f76e169bd081909f16cd8c9ee7870c |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69fde9fc184c8190bebef35df0e76076 |
completed | May 8, 2026, 1:49 p.m. |
| PD | Predicate disambiguation | batch_69fde6e5beb4819094945a695e961d88 |
completed | May 8, 2026, 1:36 p.m. |
| PDg | Predicate description generation | batch_69fde9fb68388190ada4a7018e2a2f76 |
completed | May 8, 2026, 1:49 p.m. |
Created at: May 3, 2026, 4:06 p.m.