Triple
T5156709
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1983 United Kingdom general election |
E116327
|
entity |
| Predicate | LabourVoteSwing |
P62278
|
FINISHED |
| Object | -9.3 percentage points |
—
|
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: -9.3 percentage points | Statement: [1983 United Kingdom general election, LabourVoteSwing, -9.3 percentage points]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: LabourVoteSwing Context triple: [1983 United Kingdom general election, LabourVoteSwing, -9.3 percentage points]
-
A.
numberOfVotesLabour
Indicates the total count of votes that were cast for the Labour party in a given election or voting context.
-
B.
ConservativeSeatChange
Indicates the change in the number of seats held by the Conservative party between two electoral periods.
-
C.
LiberalSeatChange
Indicates a change in the number of seats held by the Liberal party between two points in time.
-
D.
voterTurnoutChange
Indicates the amount or direction of change in voter turnout between two elections or time periods.
-
E.
electorateBehavior
Indicates how members of an electorate collectively act or decide in political contexts, such as voting patterns, preferences, or participation.
- 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_69bd445d94788190b72e2cc563120995 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd79c1354c81908176703b4853c1a4 |
completed | March 20, 2026, 4:45 p.m. |
| PD | Predicate disambiguation | batch_69bd77b0fbb88190851e2d7ae1bdcc09 |
completed | March 20, 2026, 4:37 p.m. |
| PDg | Predicate description generation | batch_69bd79bf9b088190a556dc02f10204e4 |
completed | March 20, 2026, 4:45 p.m. |
Created at: March 20, 2026, 1:44 p.m.