Triple
T28329168
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Republican Party presidential primaries, 2020 |
E717490
|
entity |
| Predicate | numberOfPledgedDelegatesWon |
P164278
|
FINISHED |
| Object | 2350+ |
—
|
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: 2350+ | Statement: [Republican Party presidential primaries, 2020, numberOfPledgedDelegatesWon, 2350+]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfPledgedDelegatesWon Context triple: [Republican Party presidential primaries, 2020, numberOfPledgedDelegatesWon, 2350+]
-
A.
pledgedDelegatesWonBy
chosen
Indicates the number of pledged delegates that have been won by a candidate or entity in a delegate-based selection process.
-
B.
numberOfDelegations
Indicates the total count of delegation instances associated with a given entity or context.
-
C.
numberOfDelegates
Indicates the quantity of delegates associated with or assigned to a particular entity or event.
-
D.
delegateCountWinner
Indicates that the referenced entity is the candidate or option that has secured the highest number of delegates in a given selection or election process.
-
E.
nonVotingDelegatesCount
Indicates the number of delegates associated with an entity who do not possess voting rights in a given decision-making process.
- F. None of above.
Provenance (3 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_69eff6e9a57c8190a69c2c74b5d72119 |
completed | April 27, 2026, 11:53 p.m. |
| NER | Named-entity recognition | batch_69ff5b233e9c8190adc06cca0758986b |
completed | May 9, 2026, 4:04 p.m. |
| PD | Predicate disambiguation | batch_69ff5a5682108190a006b23c4fcdcc7c |
completed | May 9, 2026, 4:01 p.m. |
Created at: April 28, 2026, 12:30 a.m.