Triple
T18850794
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Felipe González |
E461035
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Felipe |
—
|
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: Felipe | Statement: [Felipe González, givenName, Felipe]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Felipe Context triple: [Felipe González, givenName, Felipe]
-
A.
Felipe
chosen
Felipe is a Spanish-origin surname borne by various individuals, including the Filipino composer Julián Felipe.
-
B.
Felipe de Neve
Felipe de Neve was an 18th-century Spanish colonial governor of California best known for establishing the city of Los Angeles.
-
C.
Felipe Ángeles
Felipe Ángeles was a prominent Mexican military general and revolutionary figure who played a key role during the Mexican Revolution in the early 20th century.
-
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 is the given name of Fernando Primo de Rivera, a 19th-century Spanish general and politician who briefly served as Prime Minister of Spain.
- 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_69d8dcfa11e4819090ab1ef5bdcd2b2e |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5b8f27cf481908c60fcdce412a224 |
completed | April 20, 2026, 5:26 a.m. |
Created at: April 10, 2026, 11:56 a.m.