Triple
T29913640
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | attempted to vote for John Kasich for president in 2016 |
E759734
|
entity |
| Predicate | partyOfElector |
P178063
|
FINISHED |
| Object | Democratic Party |
—
|
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: Democratic Party | Statement: [attempted to vote for John Kasich for president in 2016, partyOfElector, Democratic Party]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: partyOfElector Context triple: [attempted to vote for John Kasich for president in 2016, partyOfElector, Democratic Party]
-
A.
partyInElection
Indicates that a political party participates as a contestant or actor in a specific election.
-
B.
partyOfCandidate
Indicates the political party with which a given candidate is affiliated.
-
C.
partyOfElectedSenator
Indicates that a given political party is the party affiliation of a specified elected senator.
-
D.
wasElectoralVehicleFor
Indicates that one entity served as the primary means, platform, or instrument through which another entity pursued electoral participation or gained electoral power.
-
E.
partnerPoliticalAffiliation
Indicates that one entity has a political affiliation that is associated with, or shared by, its partner entity.
- F. None of above. chosen
Provenance (4 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_69f2246189fc8190996b63ee1f9a2374 |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69f707f7959881908f037f0d6b1d0c36 |
completed | May 3, 2026, 8:31 a.m. |
| PD | Predicate disambiguation | batch_69f700fc274c8190a128593dc7c7abd0 |
completed | May 3, 2026, 8:02 a.m. |
| PDg | Predicate description generation | batch_69f707f380388190954b79d52a321921 |
completed | May 3, 2026, 8:31 a.m. |
Created at: April 29, 2026, 6:11 p.m.