Triple
T6496922
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fortunata y Jacinta |
E148780
|
entity |
| Predicate | placeInLiterature |
P15594
|
FINISHED |
| Object | classic of Spanish literature |
—
|
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: classic of Spanish literature | Statement: [Fortunata y Jacinta, placeInLiterature, classic of Spanish literature]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: placeInLiterature Context triple: [Fortunata y Jacinta, placeInLiterature, classic of Spanish literature]
-
A.
inLiterature
Indicates that a work, concept, or entity is mentioned, discussed, or represented within a piece of literature.
-
B.
literaryWorkInStory
Indicates that one literary work is referenced, featured, or embedded within the narrative of another story.
-
C.
literarySource
Indicates that one entity serves as the written or literary origin, reference, or basis for another entity.
-
D.
literaryThemeInvolvement
Indicates the involvement or presence of a particular literary theme within a work, passage, or character arc.
-
E.
hasLiterarySignificance
chosen
Indicates that something holds notable importance, influence, or value within the realm of literature or literary studies.
- 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_69c687e9ad288190bae5bcac9c8ac855 |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c69f386aa08190bfc8592a92ec6339 |
completed | March 27, 2026, 3:16 p.m. |
| PD | Predicate disambiguation | batch_69c68ab714908190aa7c2fbf64078e15 |
completed | March 27, 2026, 1:48 p.m. |
Created at: March 27, 2026, 1:41 p.m.