Triple
T22080464
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anne of Windy Poplars |
E545634
|
entity |
| Predicate | hasLiterarySettingType |
P19303
|
FINISHED |
| Object | small 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 town | Statement: [Anne of Windy Poplars, hasLiterarySettingType, small town]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLiterarySettingType Context triple: [Anne of Windy Poplars, hasLiterarySettingType, small town]
-
A.
hasLiterarySetting
chosen
Indicates that a literary work is set in, or primarily takes place within, a particular location or environment.
-
B.
hasLiteraryMode
Indicates that a work, text, or expression is associated with a particular literary mode (such as satire, realism, or allegory) that characterizes its style or narrative approach.
-
C.
hasLiteraryContext
Indicates that something is associated with, situated within, or explained by a particular literary context (such as a work, genre, period, or interpretive framework).
-
D.
hasLiteraryForm
Indicates that one entity is expressed, structured, or realized in a particular literary form (such as a genre, style, or textual format).
-
E.
hasFictionalSettingElement
Indicates that something includes or is associated with a specific element or component of a fictional setting.
- 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_69e11e3523488190badd54b5d580c00d |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f128b56d5c8190aa825fe02e3ad917 |
completed | April 28, 2026, 9:37 p.m. |
| PD | Predicate disambiguation | batch_69e71b20ec50819096ac196c798f8e3c |
completed | April 21, 2026, 6:37 a.m. |
Created at: April 16, 2026, 8:28 p.m.