Triple
T19612
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Democratic Party presidential primaries, 1980 |
E389
|
entity |
| Predicate | opposedIncumbentFromSameParty |
P437
|
FINISHED |
| Object | true |
—
|
LITERAL FINISHED |
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: true | Statement: [Democratic Party presidential primaries, 1980, opposedIncumbentFromSameParty, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: opposedIncumbentFromSameParty Context triple: [Democratic Party presidential primaries, 1980, opposedIncumbentFromSameParty, true]
-
A.
opposedBy
chosen
Indicates that one entity actively resists, disagrees with, or works against the actions, views, or position of another entity.
-
B.
defeatedCandidate
Indicates that one candidate has won an election or contest against another candidate, causing the other to lose.
-
C.
electedCandidate
Indicates that a particular person has been chosen as the winner in an election for a given position or office.
-
D.
electoralVoteRunnerUp
Indicates that the subject is the candidate who received the second-highest number of electoral votes in a given election.
-
E.
politicalParty
Indicates that an entity is affiliated with, belongs to, or is a member of a specific political party.
- 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_69a240778d288190815c0052ebbbcc91 |
completed | Feb. 28, 2026, 1:10 a.m. |
| NER | Named-entity recognition | batch_69a24703cb988190ad2bc181d27829e4 |
completed | Feb. 28, 2026, 1:38 a.m. |
| PD | Predicate disambiguation | batch_69a24650f1f0819081e638fafd18d687 |
completed | Feb. 28, 2026, 1:35 a.m. |
Created at: Feb. 28, 2026, 1:14 a.m.