Triple
T26263720
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2022 Kansas gubernatorial election |
E656920
|
entity |
| Predicate | tookPlaceInTraditionallyRepublicanState |
P160180
|
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: [2022 Kansas gubernatorial election, tookPlaceInTraditionallyRepublicanState, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tookPlaceInTraditionallyRepublicanState Context triple: [2022 Kansas gubernatorial election, tookPlaceInTraditionallyRepublicanState, true]
-
A.
republicanParty
Indicates that an entity is affiliated with, belongs to, or is a member/supporter of the Republican Party.
-
B.
tookPlaceInState
Indicates that an event or occurrence happened within the geographical or political boundaries of a specific state.
-
C.
numberOfStatesCarriedByRepublicanNominee
Indicates the number of U.S. states won or carried by the Republican presidential nominee in an election.
-
D.
hadRepublicanPrimary
Indicates that a Republican Party primary election was held for a given office, race, or jurisdiction.
-
E.
tookPlaceOnRepublicanDate
Indicates that an event occurred on a date expressed in the Republican (French Revolutionary) calendar.
- 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_69ee5b4e21bc819082be98bc9ab09796 |
completed | April 26, 2026, 6:37 p.m. |
| NER | Named-entity recognition | batch_69f60e022a5881908a4582d8d9cbbb38 |
completed | May 2, 2026, 2:45 p.m. |
| PD | Predicate disambiguation | batch_69f5f7ff548c8190a23e98c5e66e0bc7 |
completed | May 2, 2026, 1:11 p.m. |
| PDg | Predicate description generation | batch_69f5ffc6268c8190b63f6360ebadab73 |
completed | May 2, 2026, 1:44 p.m. |
Created at: April 26, 2026, 9:11 p.m.