Triple
T33658299
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Argylle |
E862281
|
entity |
| Predicate | featuresMetaFiction |
P165192
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Argylle, featuresMetaFiction, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresMetaFiction Context triple: [Argylle, featuresMetaFiction, yes]
-
A.
featuresFictionalForm
Indicates that one entity includes, presents, or incorporates a fictional representation or version of another entity.
-
B.
metaFictionalUniverse
Indicates that one fictional universe exists as a story, construct, or referenced fiction within another fictional universe.
-
C.
literaryFeature
Indicates a relationship where something possesses or exhibits a characteristic, device, or stylistic element used in literature.
-
D.
metafictionalRelation
chosen
Indicates a relationship in which a work, element, or narrative explicitly refers to, comments on, or otherwise draws attention to its own fictional status or construction.
-
E.
fictionalFocus
Indicates that the primary emphasis or attention within a context is placed on fictional content, elements, or aspects.
- 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_69f349840ba881908e3bfce536aeb92b |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_6a0204dafcc08190868a6f3eab162505 |
completed | May 11, 2026, 4:33 p.m. |
| PD | Predicate disambiguation | batch_6a0202dc60348190a140bb9da906f5b6 |
completed | May 11, 2026, 4:25 p.m. |
Created at: May 1, 2026, 1:42 a.m.