Triple
T4317783
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Spanish general election, April 2019 |
E96433
|
entity |
| Predicate | PPVoteSharePercentage |
P9216
|
FINISHED |
| Object | 16.7 |
—
|
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: 16.7 | Statement: [Spanish general election, April 2019, PPVoteSharePercentage, 16.7]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: PPVoteSharePercentage Context triple: [Spanish general election, April 2019, PPVoteSharePercentage, 16.7]
-
A.
popularVoteShare
chosen
Indicates the proportion of all votes cast in an election that were received by a particular candidate, party, or option.
-
B.
smithPopularVotePercentage
Indicates the percentage of the popular vote that was received by the entity named Smith in a given election or voting context.
-
C.
popularVoteShareThird
Indicates the proportion of total popular votes received by the third-place candidate or option in an election.
-
D.
voterTurnoutPercentage
Indicates the proportion of eligible or registered voters who actually cast a ballot in a given election, expressed as a percentage.
-
E.
publicVoteWeight
Indicates that an entity’s influence or impact in a public voting process is quantified by a specific weight or value.
- 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_69b345422aac81909ddbadae437d122e |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b350f883c88190a2d72f7d124eef43 |
completed | March 12, 2026, 11:49 p.m. |
| PD | Predicate disambiguation | batch_69b34f4bec888190987fc2631498b637 |
completed | March 12, 2026, 11:42 p.m. |
Created at: March 12, 2026, 11:12 p.m.