Triple
T17454762
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kupferstichkabinett |
E424999
|
entity |
| Predicate | hasWorkBy |
P12366
|
FINISHED |
| Object | Francisco de Goya |
—
|
NE NERFINISHED |
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: Francisco de Goya | Statement: [Kupferstichkabinett, hasWorkBy, Francisco de Goya]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Francisco de Goya Context triple: [Kupferstichkabinett, hasWorkBy, Francisco de Goya]
-
A.
Francisco Goya
chosen
Francisco Goya was a pioneering Spanish Romantic painter and printmaker renowned for his powerful portraits, dark and haunting imagery, and critical depictions of war and society.
-
B.
Goya Toledo
Goya Toledo is a Spanish actress and former model best known internationally for her role in the acclaimed film "Amores perros."
-
C.
Goya
Goya is Habana Labs’ AI inference processor designed to accelerate deep learning workloads with high efficiency and scalability.
-
D.
Goya
Goya is a central, upscale neighborhood in Madrid, Spain, known for its shopping streets, cultural venues, and sports arenas.
-
E.
Francisco de Pareja
Francisco de Pareja was a Spanish Franciscan missionary and linguist best known for his early 17th-century work documenting and publishing grammars and catechisms in the Timucua language of Florida.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d889db0ba481908402409af3b37917 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e4514129f08190ae7581d2915a0373 |
completed | April 19, 2026, 3:51 a.m. |
Created at: April 10, 2026, 5:47 a.m.