Triple
T2723357
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | La Maja Vestida |
E60131
|
entity |
| Predicate | associatedWithDebatesOn |
P8604
|
FINISHED |
| Object | eroticism in art |
—
|
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: eroticism in art | Statement: [La Maja Vestida, associatedWithDebatesOn, eroticism in art]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedWithDebatesOn Context triple: [La Maja Vestida, associatedWithDebatesOn, eroticism in art]
-
A.
hasDebate
chosen
Indicates that there is a formal discussion or argument between entities, typically presenting opposing viewpoints on a topic.
-
B.
hasLongTermDebateOn
Indicates that there is an ongoing, extended period of discussion, disagreement, or argument concerning a particular topic or issue.
-
C.
hasDebatedStatus
Indicates that an entity has participated in or been assigned a particular status related to a debate or debating activity.
-
D.
broadcastsDebates
Indicates that one entity transmits or airs debates for an audience, typically via a communication medium such as television, radio, or online platforms.
-
E.
enteredPoliticalDebateIn
Indicates that an entity took part in a political debate that occurred in a specified place or context.
- 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_69ab4b746d248190958e052045c09255 |
completed | March 6, 2026, 9:47 p.m. |
| NER | Named-entity recognition | batch_69abdaca581881908fe8d3d820f839b7 |
completed | March 7, 2026, 7:59 a.m. |
| PD | Predicate disambiguation | batch_69abd82586f88190a98f60d3247fe2d3 |
completed | March 7, 2026, 7:47 a.m. |
Created at: March 6, 2026, 9:55 p.m.