Triple
T24408440
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Premio FIL de Literatura en Lenguas Romances |
E615376
|
entity |
| Predicate | géneroElegible |
P125590
|
FINISHED |
| Object | narrativa |
—
|
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: narrativa | Statement: [Premio FIL de Literatura en Lenguas Romances, géneroElegible, narrativa]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: géneroElegible Context triple: [Premio FIL de Literatura en Lenguas Romances, géneroElegible, narrativa]
-
A.
hasGenreEligibility
chosen
Indicates that an entity qualifies to be categorized under a particular genre according to defined criteria.
-
B.
hasGenderNeutralEligibility
Indicates that an entity is eligible or applicable in a way that does not depend on or specify a particular gender.
-
C.
hasPerformerGender
Indicates that an action, event, or performance is associated with the gender of the performer who carries it out.
-
D.
featuredGender
Indicates that a particular gender is highlighted, emphasized, or given primary focus in a given context or presentation.
-
E.
genderTarget
Indicates that an action, message, or effect is specifically directed toward entities of a particular gender.
- 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_69e2d7e780bc81908049c779e697a7f6 |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f2957fab0481909121c6da6b5e34c0 |
completed | April 29, 2026, 11:34 p.m. |
| PD | Predicate disambiguation | batch_69f287cc4fd4819081e93cc638d9512d |
completed | April 29, 2026, 10:35 p.m. |
Created at: April 18, 2026, 2:05 a.m.