Triple
T34883413
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1970 United States Senate campaign in Michigan |
E1006073
|
entity |
| Predicate | hasElectionYear |
P187415
|
FINISHED |
| Object | 1970 |
—
|
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: 1970 | Statement: [1970 United States Senate campaign in Michigan, hasElectionYear, 1970]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasElectionYear Context triple: [1970 United States Senate campaign in Michigan, hasElectionYear, 1970]
-
A.
appliesToElectionYear
Indicates that something is relevant, valid, or in effect specifically for a given election year.
-
B.
hasElectionsFor
Indicates that a governing body, jurisdiction, or organization conducts elections to select or appoint members to a specified office, role, or representative body.
-
C.
hasElection
Indicates that an entity conducts, holds, or is associated with an election event.
-
D.
reElectionYear
Indicates the year in which an entity is (or is scheduled to be) elected again to the same position or office.
-
E.
targetedOfficeElectionYear
Indicates the year in which the election is held for the office that is the target of the relationship.
- 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_69f76dbedb288190afe5780710847410 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69fb563aec448190875410fb1a3ed624 |
completed | May 6, 2026, 2:54 p.m. |
| PD | Predicate disambiguation | batch_69fb35b9ede881908aaae93a215525df |
completed | May 6, 2026, 12:36 p.m. |
| PDg | Predicate description generation | batch_69fb563a28d88190b28345c465c545f8 |
completed | May 6, 2026, 2:54 p.m. |
Created at: May 3, 2026, 4 p.m.