Triple
T19903585
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tea Party movement |
E478354
|
entity |
| Predicate | helpedElect |
P33868
|
FINISHED |
| Object | Marco 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 Rubio | Statement: [Tea Party movement, helpedElect, Marco Rubio]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Marco Rubio Context triple: [Tea Party movement, helpedElect, Marco 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.
Rubio
Rubio is a Spanish professional basketball player known for his exceptional playmaking and court vision as an NBA point guard.
-
C.
Carlos A. Curbelo
Carlos A. Curbelo was a Uruguayan naval officer honored by having an international airport in Uruguay named after him.
-
D.
Marco Ramos Rubio
Marco Ramos Rubio is a son of Spanish footballer Sergio Ramos.
-
E.
Ted Cruz
Ted Cruz is a conservative Republican politician and lawyer who has served as a U.S. senator and was a prominent candidate in the 2016 presidential election.
- 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_69d8e520682081909892916424699bd5 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e65944c55481909b54a8f9a9c087d6 |
completed | April 20, 2026, 4:50 p.m. |
Created at: April 10, 2026, 1:52 p.m.