Triple
T20112865
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marco Rubio Rivera |
E490376
|
entity |
| Predicate | birthName |
P65
|
FINISHED |
| Object | Marco Antonio Rubio |
—
|
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: Marco Antonio Rubio | Statement: [Marco Rubio Rivera, birthName, Marco Antonio Rubio]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Marco Antonio Rubio Context triple: [Marco Rubio Rivera, birthName, Marco Antonio Rubio]
-
A.
Marco Rubio
chosen
Marco Rubio is an American politician serving as a U.S. Senator from Florida and a prominent figure in the Republican Party.
-
B.
Marco Ramos Rubio
Marco Ramos Rubio is a son of Spanish footballer Sergio Ramos.
-
C.
Carlos A. Curbelo
Carlos A. Curbelo was a Uruguayan naval officer honored by having an international airport in Uruguay named after him.
-
D.
Rubio
Rubio is a Spanish professional basketball player known for his exceptional playmaking and court vision as an NBA point guard.
-
E.
Charlie Crist
Charlie Crist is an American politician who has served as both a Republican and Democratic governor of Florida and later as a member of the U.S. House of Representatives.
- 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_69da62636cc08190982cc71733a17b8d |
completed | April 11, 2026, 3:01 p.m. |
| NER | Named-entity recognition | batch_69e666e21f908190b46c747662ff378a |
completed | April 20, 2026, 5:48 p.m. |
Created at: April 11, 2026, 11:29 p.m.