Triple
T5361682
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | United Kingdom general election, 1929 |
E103034
|
entity |
| Predicate | ConservativePopularVote |
P59396
|
FINISHED |
| Object | 8,656,944 |
—
|
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: 8,656,944 | Statement: [United Kingdom general election, 1929, ConservativePopularVote, 8,656,944]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ConservativePopularVote Context triple: [United Kingdom general election, 1929, ConservativePopularVote, 8,656,944]
-
A.
conservativePopularVotePercentage
Indicates the percentage of the total popular vote that was received by the Conservative party in a given election or contest.
-
B.
numberOfVotesConservative
chosen
Indicates the number of votes that were cast for the Conservative option or party in a given context.
-
C.
ConservativeVoteSwing
Indicates a change in the level of electoral support for the Conservative party between two points in time or between two elections.
-
D.
ConservativeSeatsWon
Indicates the number of parliamentary or legislative seats won by the Conservative party in an election.
-
E.
republicanPopularVoteShare
Indicates the proportion of total votes in an election that were cast for the Republican Party.
- 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_69bd43daa3e4819090b59d127db70e57 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd865a0bb081909579cfe7c7974075 |
completed | March 20, 2026, 5:39 p.m. |
| PD | Predicate disambiguation | batch_69bd845f41f88190b75b8b64b9e41862 |
completed | March 20, 2026, 5:31 p.m. |
Created at: March 20, 2026, 2:02 p.m.