Triple
T6699243
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Carybé |
E152834
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Bernabó |
E558948
|
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: Bernabó | Statement: [Carybé, familyName, Bernabó]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bernabó Context triple: [Carybé, familyName, Bernabó]
-
A.
Bernabó
chosen
Bernabó is the Italian-origin surname of the Argentine-Brazilian artist and illustrator known as Carybé (Héctor Julio Páride Bernabó).
-
B.
Antonio Vandone di Cortemilia
Antonio Vandone di Cortemilia was an Italian architect known for designing the Mogadishu Cathedral in Somalia during the colonial era.
-
C.
Malatesta
Malatesta is an Italian surname most famously associated with Errico Malatesta, a prominent anarchist thinker and activist of the late 19th and early 20th centuries.
-
D.
Tebald
Tebald is a masculine given name of medieval European origin, from which the modern short form "Tibbets" is derived.
-
E.
Gualtiero
Gualtiero is an Italian given name equivalent to the English name Walter.
- 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_69c68807adbc8190b8632df42b39eda0 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d0a7355081908a0acfa8d2bb4c09 |
completed | March 27, 2026, 6:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c6f7bfcb048190b682f4ec7e404b3e |
completed | March 27, 2026, 9:33 p.m. |
Created at: March 27, 2026, 2:05 p.m.