Triple
T15496033
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1963 Chicago mayoral election |
E378819
|
entity |
| Predicate | percentageOfVoteForRichard J. Daley |
P118474
|
FINISHED |
| Object | 58.83% |
—
|
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: 58.83% | Statement: [1963 Chicago mayoral election, percentageOfVoteForRichard J. Daley, 58.83%]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: percentageOfVoteForRichard J. Daley Context triple: [1963 Chicago mayoral election, percentageOfVoteForRichard J. Daley, 58.83%]
-
A.
WillkiePopularVotes
Indicates the number of popular votes received by Willkie in a given election or electoral context.
-
B.
popularVoteForThomasEDewey
Indicates that the popular vote in an election was cast in favor of Thomas E. Dewey.
-
C.
popularVotesForHoratio Seymour
Indicates the number of popular votes that were cast in favor of Horatio Seymour in an election.
-
D.
wonFirstDemocraticElection
Indicates that the subject achieved victory in the first democratic election held for a given office, position, or context.
-
E.
RobertMLaFollettePopularVoteShare
Indicates the proportion of the total popular vote that was received by Robert M. La Follette in a given election or electoral context.
- 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_69d85cd53a7c819080f5b9042c4c199e |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e03faecd60819091eeaa56c9c8f67d |
completed | April 16, 2026, 1:47 a.m. |
| PD | Predicate disambiguation | batch_69ded2874b788190999158e0f043be21 |
completed | April 14, 2026, 11:49 p.m. |
| PDg | Predicate description generation | batch_69ded5deee00819099fa3e43313312e1 |
completed | April 15, 2026, 12:03 a.m. |
Created at: April 10, 2026, 3:52 a.m.