Triple
T8646326
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2017 United Kingdom general election |
E204985
|
entity |
| Predicate | liberalDemocratNetSeatChange |
P84104
|
FINISHED |
| Object | +4 |
—
|
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: +4 | Statement: [2017 United Kingdom general election, liberalDemocratNetSeatChange, +4]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: liberalDemocratNetSeatChange Context triple: [2017 United Kingdom general election, liberalDemocratNetSeatChange, +4]
-
A.
LiberalSeatChange
Indicates a change in the number of seats held by the Liberal party between two points in time.
-
B.
ConservativeSeatChange
Indicates the change in the number of seats held by the Conservative party between two electoral periods.
-
C.
DemocraticSeatChange
Indicates the change in the number of seats held by the Democratic Party between two specified electoral outcomes or time points.
-
D.
LiberalSeatsWon
Indicates the number of parliamentary or legislative seats won by the Liberal party in an election.
-
E.
LabourSeatsWon
Indicates the number of parliamentary seats won by the Labour Party in an election.
- 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_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. |
| PDg | Predicate description generation | batch_69cc473e44988190a3b02498e5fff668 |
completed | March 31, 2026, 10:14 p.m. |
Created at: March 30, 2026, 6:28 p.m.