Triple
T29943965
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | United States Senate election in Connecticut, 2022 |
E760579
|
entity |
| Predicate | levyEndorsement |
P168282
|
FINISHED |
| Object | Donald Trump |
—
|
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: Donald Trump | Statement: [United States Senate election in Connecticut, 2022, levyEndorsement, Donald Trump]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: levyEndorsement Context triple: [United States Senate election in Connecticut, 2022, levyEndorsement, Donald Trump]
-
A.
canLevy
Indicates that an entity has the authority or power to impose and collect a charge, tax, or fine on another entity or resource.
-
B.
endorsedAt
Indicates the specific time or date at which an endorsement or approval of something was made.
-
C.
hasRegionalEndorsement
Indicates that an entity has received an official endorsement or approval from a specific regional authority or organization.
-
D.
endorsedBy
Indicates that one entity has given formal approval, support, or recommendation to another entity.
-
E.
voterApproval
Indicates that a voter has given consent, support, or positive endorsement to a proposal, candidate, or decision.
- 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_69f22463f3648190a603c3ff305c660b |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69f6780a76b0819091e8781ee21191ac |
completed | May 2, 2026, 10:17 p.m. |
| PD | Predicate disambiguation | batch_69f66ec8298c8190b41fe9d182c05676 |
completed | May 2, 2026, 9:38 p.m. |
| PDg | Predicate description generation | batch_69f67256d064819094be04fc1bbbc635 |
completed | May 2, 2026, 9:53 p.m. |
Created at: April 29, 2026, 6:23 p.m.