Triple
T8646321
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2017 United Kingdom general election |
E204985
|
entity |
| Predicate | greenPartyOfEnglandAndWalesSeatsWon |
P23397
|
FINISHED |
| Object | 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: 1 | Statement: [2017 United Kingdom general election, greenPartyOfEnglandAndWalesSeatsWon, 1]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: greenPartyOfEnglandAndWalesSeatsWon Context triple: [2017 United Kingdom general election, greenPartyOfEnglandAndWalesSeatsWon, 1]
-
A.
greenPartyFirstMP
Indicates that the person is the first Member of Parliament elected from the Green Party in a given political context or jurisdiction.
-
B.
seatsWonByGreenParty
chosen
Indicates the number of legislative or electoral seats that were won by the Green Party in a given election or governing body.
-
C.
greenPartyPopularVotePercentage
Indicates the proportion of total votes in an election that were cast for the Green Party, expressed as a percentage.
-
D.
numberOfSeatsWonIn2019ParliamentaryElection
Indicates the number of seats an entity won in the 2019 parliamentary election.
-
E.
LabourSeatsWon
Indicates the number of parliamentary seats won by the Labour Party in an election.
- 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.