Triple
T16141456
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | wizard of Alderley Edge |
E391663
|
entity |
| Predicate | hasTrope |
P68123
|
FINISHED |
| Object | king in the mountain |
—
|
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: king in the mountain | Statement: [wizard of Alderley Edge, hasTrope, king in the mountain]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTrope Context triple: [wizard of Alderley Edge, hasTrope, king in the mountain]
-
A.
usedAsTrope
chosen
Indicates that something functions as a recurring narrative device, motif, or cliché within a story or set of stories.
-
B.
inspiredTrope
Indicates that one trope serves as the creative or conceptual inspiration for another trope.
-
C.
subvertsTrope
Indicates that one entity challenges, undermines, or reverses the expected pattern or convention represented by a particular trope.
-
D.
hasIronicMeaning
Indicates that something conveys a meaning opposite to or incongruent with its literal expression, creating an ironic effect.
-
E.
hasDramaticTechnique
Indicates that one entity employs, features, or is characterized by a particular dramatic technique associated with 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_69d87f1c65e48190aa2b4c472e9bafc4 |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e21a087c848190aba9ed2ccb422427 |
completed | April 17, 2026, 11:31 a.m. |
| PD | Predicate disambiguation | batch_69e182885bc08190822ae7e8a4b8ac1f |
completed | April 17, 2026, 12:44 a.m. |
Created at: April 10, 2026, 5:01 a.m.