Triple
T20527473
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2018 Florida gubernatorial election |
E503974
|
entity |
| Predicate | hadRepublicanPrimary |
P140433
|
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: [2018 Florida gubernatorial election, hadRepublicanPrimary, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hadRepublicanPrimary Context triple: [2018 Florida gubernatorial election, hadRepublicanPrimary, true]
-
A.
RepublicanPrimaryCandidate
Indicates that an individual is a candidate running in a Republican Party primary election for a particular office.
-
B.
republicanNominee
Indicates that the subject is the officially selected Republican Party candidate for the specified office or election.
-
C.
republicanPrimaryStartDate
Indicates the date on which a Republican Party primary election begins.
-
D.
wonPrimary
Indicates that a candidate secured victory in a primary election against their competitors.
-
E.
ranPresidentialCandidate
Indicates that the subject has been a candidate in a presidential election.
- 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_69e0b4b3a6e08190ae663701f50fab8e |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6a0677018819085396cc8795a34e9 |
completed | April 20, 2026, 9:53 p.m. |
| PD | Predicate disambiguation | batch_69e59fdb7ad88190924176c32a195db3 |
completed | April 20, 2026, 3:39 a.m. |
| PDg | Predicate description generation | batch_69e5a6a824748190bbe6192d73f3c613 |
completed | April 20, 2026, 4:08 a.m. |
Created at: April 16, 2026, 11:37 a.m.