Triple
T13220379
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fiasco |
E314735
|
entity |
| Predicate | literaryAnalysisFocus |
P36841
|
FINISHED |
| Object | representation of totalitarian systems |
—
|
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: representation of totalitarian systems | Statement: [Fiasco, literaryAnalysisFocus, representation of totalitarian systems]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: literaryAnalysisFocus Context triple: [Fiasco, literaryAnalysisFocus, representation of totalitarian systems]
-
A.
literaryFeature
Indicates a relationship where something possesses or exhibits a characteristic, device, or stylistic element used in literature.
-
B.
literarySubject
chosen
Indicates that one entity serves as the subject, topic, or focus of a literary work created by another entity.
-
C.
literaryPurpose
Indicates the intended function, effect, or communicative goal that a text or passage is meant to achieve within a literary context.
-
D.
literaryCriticismType
Indicates the specific kind or category of literary criticism applied to a work, author, or text.
-
E.
literaryInterest
Indicates that one entity has an interest in, appreciation of, or engagement with the literary works or writings of 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_69d806affc688190a25b6ccc588e9c72 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98cf581508190883033f0c961736a |
completed | April 10, 2026, 11:51 p.m. |
| PD | Predicate disambiguation | batch_69d98bc938f081909f123bdf1263ff7f |
completed | April 10, 2026, 11:46 p.m. |
Created at: April 9, 2026, 9:18 p.m.