Triple
T29913670
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | attempted to vote for John Kasich for president in 2016 |
E759734
|
entity |
| Predicate | electorHomeState |
P562
|
FINISHED |
| Object | Colorado |
—
|
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: Colorado | Statement: [attempted to vote for John Kasich for president in 2016, electorHomeState, Colorado]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: electorHomeState Context triple: [attempted to vote for John Kasich for president in 2016, electorHomeState, Colorado]
-
A.
vicePresidentElectHomeState
Indicates the home state associated with a person who is the vice president-elect.
-
B.
homeState
chosen
Indicates that a person or organization has their primary residence, registration, or official base in a particular state.
-
C.
candidateRepresentedState
Indicates that a political candidate officially represents or runs for office on behalf of a particular state.
-
D.
representedState
Indicates that one entity serves as a representation or depiction of the state or condition of another entity.
-
E.
stateRepresentedInPolitics
Indicates that a political entity or interest is represented within the political system or decision-making structures of a given state.
- F. None of above.
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_69f2246189fc8190996b63ee1f9a2374 |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69fd9ff026a48190bfec33deeb3b2c43 |
completed | May 8, 2026, 8:33 a.m. |
| PD | Predicate disambiguation | batch_69fd97d805bc8190ba12f429d3ad04c7 |
completed | May 8, 2026, 7:59 a.m. |
Created at: April 29, 2026, 6:11 p.m.