Triple
T34910968
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2014 Connecticut gubernatorial election |
E1006863
|
entity |
| Predicate | winningTicketParty |
P6362
|
FINISHED |
| Object | Democratic Party (United States) |
—
|
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 (United States) | Statement: [2014 Connecticut gubernatorial election, winningTicketParty, Democratic Party (United States)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: winningTicketParty Context triple: [2014 Connecticut gubernatorial election, winningTicketParty, Democratic Party (United States)]
-
A.
winnerParty
chosen
Indicates the political party that has won a particular election, contest, or decision-making process.
-
B.
winnerPartyRegistration
Indicates the political party affiliation under which the winning candidate in an election was registered.
-
C.
leadingFigureOfWinningParty
Indicates that a person is the primary leader of the political party that has won an election or governing contest.
-
D.
runnerUpParty
Indicates the political party that finished in second place in an election or contest.
-
E.
winnerAssociated
Indicates that there is a relevant connection or affiliation between a winner and another entity in the context of a particular event or competition.
- 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_69f76dc1b4a081909b4c6e4d8ec0aa2d |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f782c98fa08190870b68de2c1ff26a |
completed | May 3, 2026, 5:15 p.m. |
| PD | Predicate disambiguation | batch_69f781020cc4819088c40cb8589504e4 |
completed | May 3, 2026, 5:08 p.m. |
Created at: May 3, 2026, 4 p.m.