Triple
T17580063
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Israeli legislative election, 1969 |
E428176
|
entity |
| Predicate | party1VoteShare |
P9216
|
FINISHED |
| Object | 46.2% |
—
|
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: 46.2% | Statement: [Israeli legislative election, 1969, party1VoteShare, 46.2%]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: party1VoteShare Context triple: [Israeli legislative election, 1969, party1VoteShare, 46.2%]
-
A.
rulingPartyPopularVotePercentage
Indicates the percentage of the total popular vote received by the party currently in power or holding the ruling position.
-
B.
AlliancePopularVoteShare
Indicates the proportion of total votes received by a political alliance in an election relative to all valid votes cast.
-
C.
popularVoteShare
chosen
Indicates the proportion of all votes cast in an election that were received by a particular candidate, party, or option.
-
D.
presidentialVoteShareWinner
Indicates that the subject is the candidate (or party) who received the highest share of votes in a presidential election within the specified context.
-
E.
MapaiVoteShare
Indicates the proportion of total votes that were cast in favor of the Mapai party in a given election or electoral context.
- 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_69d889e1030481909950e140c63255b9 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e463cdb1608190a7e249ad6531b1dc |
completed | April 19, 2026, 5:10 a.m. |
| PD | Predicate disambiguation | batch_69e3b4fd7d048190b54ee4c6155612a5 |
completed | April 18, 2026, 4:44 p.m. |
Created at: April 10, 2026, 5:50 a.m.