Triple
T16246935
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | José Miguel Cabrera Torres |
E394394
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Cabrera |
E393247
|
NE 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: Cabrera | Statement: [José Miguel Cabrera Torres, familyName, Cabrera]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cabrera Context triple: [José Miguel Cabrera Torres, familyName, Cabrera]
-
A.
Cabrera
Cabrera is a small, sparsely populated island and national park in the Mediterranean Sea, known for its unspoiled natural landscapes and rich marine biodiversity.
-
B.
Cabrera
chosen
Cabrera is a Spanish-origin surname borne by numerous notable individuals across sports, arts, and public life.
-
C.
Cabrera
Cabrera is a rural municipality in Colombia’s Cundinamarca Department, known for its mountainous Andean landscapes and proximity to the Sumapaz páramo region.
-
D.
Francisco Cabrera
Francisco Cabrera is a personal name shared by multiple individuals, most commonly associated with Spanish-speaking figures in fields such as politics, sports, and the arts.
-
E.
Luis Cabrera
Luis Cabrera is a relatively common Spanish-language personal name shared by multiple notable individuals across fields such as politics, sports, and the arts.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d87f2171208190951025e526947816 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e245931074819096f38003da70f271 |
completed | April 17, 2026, 2:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a001f8ae4288190b59e4af3e3d95000 |
completed | May 10, 2026, 6:02 a.m. |
Created at: April 10, 2026, 5:04 a.m.