Triple
T16186686
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | United Kingdom general election, 1966 |
E392821
|
entity |
| Predicate | percentageVoteLiberals |
P40761
|
FINISHED |
| Object | 9.1% |
—
|
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: 9.1% | Statement: [United Kingdom general election, 1966, percentageVoteLiberals, 9.1%]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: percentageVoteLiberals Context triple: [United Kingdom general election, 1966, percentageVoteLiberals, 9.1%]
-
A.
popularVoteShareLiberals
chosen
Indicates the proportion of the total popular vote that was received by the Liberal party or liberal candidates in an election.
-
B.
LiberalPopularVote
Indicates that the Liberal party received a high or majority share of the popular vote in an election.
-
C.
conservativePopularVotePercentage
Indicates the percentage of the total popular vote that was received by the Conservative party in a given election or contest.
-
D.
popularVoteShare
Indicates the proportion of all votes cast in an election that were received by a particular candidate, party, or option.
-
E.
numberOfVotesConservative
Indicates the number of votes that were cast for the Conservative option or party in a given context.
- 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_69d87f1e49ac8190a311b54d32990576 |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e22061f47481909ededd5eed40f5a4 |
completed | April 17, 2026, 11:58 a.m. |
| PD | Predicate disambiguation | batch_69e219e11f6081909106b1240a17fd37 |
completed | April 17, 2026, 11:30 a.m. |
Created at: April 10, 2026, 5:02 a.m.