Triple
T21115138
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1792 United States presidential election |
E520275
|
entity |
| Predicate | wasSecondPresidentialElection |
P142911
|
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: [1792 United States presidential election, wasSecondPresidentialElection, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wasSecondPresidentialElection Context triple: [1792 United States presidential election, wasSecondPresidentialElection, true]
-
A.
wasFirstPresidentialElectionAfter
Indicates that one presidential election was the first to occur after another specified presidential election.
-
B.
wasFirstDirectPresidentialVoteSince
Indicates that a given presidential vote was the first direct presidential election to occur since a specified prior event or point in time.
-
C.
inceptionOfSecondPresidency
Indicates the event or point in time when an entity begins its second term in a presidential office.
-
D.
wonPresidentialElection
Indicates that one entity achieved victory over others in a presidential election.
-
E.
secondPresident
Indicates that the subject is the second person to hold the office of president of the specified entity or organization.
- 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_69e0b509a318819092fbbcb21d1fe603 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e72105bd648190beecc636284397bd |
completed | April 21, 2026, 7:02 a.m. |
| PD | Predicate disambiguation | batch_69e5dbff56848190a03b350a9305c612 |
completed | April 20, 2026, 7:55 a.m. |
| PDg | Predicate description generation | batch_69e5e2e03d88819086f8b641656ad8b0 |
completed | April 20, 2026, 8:25 a.m. |
Created at: April 16, 2026, 2:54 p.m.