Triple
T37691917
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Austrian legislative election 2019 |
E938827
|
entity |
| Predicate | secondLargestPartyVoteShare |
P73163
|
FINISHED |
| Object | 21.2% |
—
|
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: 21.2% | Statement: [Austrian legislative election 2019, secondLargestPartyVoteShare, 21.2%]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: secondLargestPartyVoteShare Context triple: [Austrian legislative election 2019, secondLargestPartyVoteShare, 21.2%]
-
A.
secondLargestParty
Indicates that the subject is the political party with the second-highest level of support, representation, or size within a specified political context.
-
B.
secondLargestPartySeatsWon
Indicates the number of seats won by the political party that finished second in size or vote share in an election.
-
C.
secondPartyPopularVoteShare
chosen
Indicates the proportion of total popular votes received by the second party in an election.
-
D.
sixthLargestPartyVoteSharePercentage
Indicates the percentage of total votes received by the sixth-largest political party in an election.
-
E.
secondRoundVoteShareOf
Indicates the proportion of total votes an entity receives in the second round of a multi-round voting or election process.
- 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_69f76eda6ae48190b3111071eeacc038 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69ffaa7bc45c8190b907db8579244a7b |
completed | May 9, 2026, 9:43 p.m. |
| PD | Predicate disambiguation | batch_69ffa9f6c9a481908fbd4d18b311cbe2 |
completed | May 9, 2026, 9:41 p.m. |
Created at: May 3, 2026, 4:18 p.m.