Triple
T17520010
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Typer |
E426658
|
entity |
| Predicate | creator |
P184
|
FINISHED |
| Object | Sebastián Ramírez |
—
|
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: Sebastián Ramírez | Statement: [Typer, creator, Sebastián Ramírez]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sebastián Ramírez Context triple: [Typer, creator, Sebastián Ramírez]
-
A.
Sebastián Ramírez
chosen
Sebastián Ramírez is a software developer best known for creating the modern, high-performance Python web framework FastAPI.
-
B.
Andrés Pinzón
Andrés Pinzón is a person notable enough to be specifically cited as a bearer of the surname Pinzón.
-
C.
Miguel Pinzón
Miguel Pinzón is a Colombian actor and television personality known for his roles in Spanish-language telenovelas and series.
-
D.
Dante Aristizábal Martínez
Dante Aristizábal Martínez is one of the children of Colombian rock musician and singer-songwriter Juanes.
-
E.
Francisco Márquez
Francisco Márquez was a young Mexican military cadet and one of the famed Niños Héroes who died defending Chapultepec Castle during the Mexican–American War.
- 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_69d889de677081909b22d2657b1f0292 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e452d18c1c81908bb843bbddb44ca1 |
completed | April 19, 2026, 3:58 a.m. |
Created at: April 10, 2026, 5:49 a.m.