Triple
T12959804
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sarrasine |
E310109
|
entity |
| Predicate | literaryAnalysis |
P36841
|
FINISHED |
| Object | subject of Roland Barthes essay S/Z |
—
|
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: subject of Roland Barthes essay S/Z | Statement: [Sarrasine, literaryAnalysis, subject of Roland Barthes essay S/Z]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: literaryAnalysis Context triple: [Sarrasine, literaryAnalysis, subject of Roland Barthes essay S/Z]
-
A.
literarySubject
chosen
Indicates that one entity serves as the subject, topic, or focus of a literary work created by another entity.
-
B.
literaryLanguage
Indicates that an entity is expressed, written, or communicated using a particular literary or standardized written language.
-
C.
inLiterature
Indicates that a work, concept, or entity is mentioned, discussed, or represented within a piece of literature.
-
D.
literaryCriticismType
Indicates the specific kind or category of literary criticism applied to a work, author, or text.
-
E.
literaryFeature
Indicates a relationship where something possesses or exhibits a characteristic, device, or stylistic element used in literature.
- 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_69d7bdfb57a88190836b743e2825feca |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d97e59a4c88190907d05b8d57dae89 |
completed | April 10, 2026, 10:48 p.m. |
| PD | Predicate disambiguation | batch_69d97dba57988190b786ffed55687a72 |
completed | April 10, 2026, 10:46 p.m. |
Created at: April 9, 2026, 5:44 p.m.