Triple
T3952122
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alfonso Arau |
E84887
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Alfonso |
E162427
|
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: Alfonso | Statement: [Alfonso Arau, givenName, Alfonso]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Alfonso Context triple: [Alfonso Arau, givenName, Alfonso]
-
A.
Alfonso
chosen
Alfonso is a masculine given name of Spanish and Italian origin historically borne by numerous kings, nobles, and notable figures across Europe.
-
B.
X Alfonso
X Alfonso is a Cuban musician and cultural entrepreneur best known for his influential role in Havana’s contemporary arts scene.
-
C.
Fernando
Fernando is the given name of Fernando Primo de Rivera, a 19th-century Spanish general and politician who briefly served as Prime Minister of Spain.
-
D.
Fernando
"Fernando" is a popular 1976 ballad by Swedish pop group ABBA, known for its nostalgic, storytelling lyrics and melodic harmonies.
-
E.
Fernando
Fernando was the given name of the Duke of Alba who served as governor-general, a prominent Spanish noble and military leader.
- 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_69aed934fbfc8190847068e4546de963 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aef939d1308190930dc2c8272eafa4 |
completed | March 9, 2026, 4:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b595f59e908190a45b3b9c767974fb |
completed | March 14, 2026, 5:08 p.m. |
Created at: March 9, 2026, 3:30 p.m.