Triple
T752950
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nueva gramática de la lengua española |
E15489
|
entity |
| Predicate | tema |
P450
|
FINISHED |
| Object | gramática del español |
—
|
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: gramática del español | Statement: [Nueva gramática de la lengua española, tema, gramática del español]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tema Context triple: [Nueva gramática de la lengua española, tema, gramática del español]
-
A.
theme
Indicates the entity that is the primary participant or content affected or characterized by an action, event, or state.
-
B.
notableTheme
Indicates that a particular theme is prominently featured in, or strongly associated with, an entity such as a work, event, or body of content.
-
C.
themeExamples
Indicates that the related entity serves as an example or illustration of the theme expressed by the subject.
-
D.
title
Indicates that one entity serves as the formal name or designation of another entity.
-
E.
subjectMatter
chosen
Indicates the topic, theme, or content area that something (such as a work, document, or discussion) is about.
- 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_69a493599a0081908da65f3407af1ef2 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a64d7d2c8190a6059adcb8fbd34f |
completed | March 1, 2026, 8:49 p.m. |
| PD | Predicate disambiguation | batch_69a4a501c4cc81908de6d63e3d4f60d7 |
completed | March 1, 2026, 8:43 p.m. |
Created at: March 1, 2026, 7:37 p.m.