Triple
T4407153
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Portuguese presidential election, 1976 |
E93761
|
entity |
| Predicate | mainOpponentVoteShare |
P47361
|
FINISHED |
| Object | 16.46% |
—
|
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: 16.46% | Statement: [Portuguese presidential election, 1976, mainOpponentVoteShare, 16.46%]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainOpponentVoteShare Context triple: [Portuguese presidential election, 1976, mainOpponentVoteShare, 16.46%]
-
A.
popularVoteShare
Indicates the proportion of all votes cast in an election that were received by a particular candidate, party, or option.
-
B.
oppositionPercentage
Indicates the proportion of entities or participants that are in opposition to a given proposal, action, or subject relative to the whole.
-
C.
opponentElectoralVotes
Indicates the number of electoral votes received by the opposing candidate or party in an election.
-
D.
percentageMainOpponent
chosen
Indicates the proportion, expressed as a percentage, that a main opponent represents relative to a defined total or context.
-
E.
popularVoteShareThird
Indicates the proportion of total popular votes received by the third-place candidate or option 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_69b345158c748190a2c040fce2da9980 |
completed | March 12, 2026, 10:58 p.m. |
| NER | Named-entity recognition | batch_69b3548b1ca08190b3136867c7098d86 |
completed | March 13, 2026, 12:04 a.m. |
| PD | Predicate disambiguation | batch_69b34f5b36a881909bf2e970aa523390 |
completed | March 12, 2026, 11:42 p.m. |
Created at: March 12, 2026, 11:28 p.m.