Triple
T8646323
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2017 United Kingdom general election |
E204985
|
entity |
| Predicate | conservativeNetSeatChange |
P20306
|
FINISHED |
| Object | -13 |
—
|
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: -13 | Statement: [2017 United Kingdom general election, conservativeNetSeatChange, -13]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: conservativeNetSeatChange Context triple: [2017 United Kingdom general election, conservativeNetSeatChange, -13]
-
A.
ConservativeSeatChange
chosen
Indicates the change in the number of seats held by the Conservative party between two electoral periods.
-
B.
ConservativeSeatsWon
Indicates the number of parliamentary or legislative seats won by the Conservative party in an election.
-
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.
numberOfVotesConservative
Indicates the number of votes that were cast for the Conservative option or party in a given context.
-
E.
DemocraticSeatChange
Indicates the change in the number of seats held by the Democratic Party between two specified electoral outcomes or time points.
- 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_69ca834e56848190abb0eeaec9dedd32 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc480eb7f88190a38d2150976cd47f |
completed | March 31, 2026, 10:17 p.m. |
| PD | Predicate disambiguation | batch_69cc45619460819091e83ffdec99c865 |
completed | March 31, 2026, 10:06 p.m. |
Created at: March 30, 2026, 6:28 p.m.