Triple
T241791
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hillary Clinton 2016 presidential campaign |
E4945
|
entity |
| Predicate | popularVoteShare |
P9216
|
FINISHED |
| Object | 48.2% |
—
|
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: 48.2% | Statement: [Hillary Clinton 2016 presidential campaign, popularVoteShare, 48.2%]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: popularVoteShare Context triple: [Hillary Clinton 2016 presidential campaign, popularVoteShare, 48.2%]
-
A.
popularVoteWinner
Indicates that the subject is the candidate who received the highest number of individual votes cast by the electorate in an election.
-
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.
popularVoteRole
Indicates the role or capacity in which an entity participates in or is associated with a popular vote.
-
D.
smithPopularVote
Indicates that Smith received a specified number or share of votes in a popular vote election or ballot.
-
E.
popularVoteRunnerUp
Indicates that one entity is the candidate who received the second-highest number of votes in a popular vote for the other entity’s election or contest.
- 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_69a257c3d0708190b0871c4269d273e6 |
completed | Feb. 28, 2026, 2:49 a.m. |
| NER | Named-entity recognition | batch_69a25d35aa288190966b6e15af1525cb |
completed | Feb. 28, 2026, 3:12 a.m. |
| PD | Predicate disambiguation | batch_69a25b60ad308190b12f119960a8bde7 |
completed | Feb. 28, 2026, 3:05 a.m. |
| PDg | Predicate description generation | batch_69a25d3463648190ac716d7475378536 |
completed | Feb. 28, 2026, 3:12 a.m. |
Created at: Feb. 28, 2026, 2:53 a.m.