Triple
T21011421
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1997 Irish presidential election |
E517557
|
entity |
| Predicate | firstPreferenceVoteShareOfAdnanAl-Kaissie |
P9216
|
FINISHED |
| Object | 4.7% |
—
|
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: 4.7% | Statement: [1997 Irish presidential election, firstPreferenceVoteShareOfAdnanAl-Kaissie, 4.7%]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstPreferenceVoteShareOfAdnanAl-Kaissie Context triple: [1997 Irish presidential election, firstPreferenceVoteShareOfAdnanAl-Kaissie, 4.7%]
-
A.
numberOfVotesWonByHamas
Indicates the quantity of votes that were cast in favor of Hamas in a given election or voting event.
-
B.
AKPVoteShare
Indicates the proportion of total votes received by the AKP in a given election or electoral unit.
-
C.
voteShareOfAbdelFattahElSisi
Indicates the proportion of total votes that were cast in favor of Abdel Fattah El-Sisi in a given election or voting context.
-
D.
popularVoteShare
chosen
Indicates the proportion of all votes cast in an election that were received by a particular candidate, party, or option.
-
E.
firstBallotCandidate
Indicates that the entity was a candidate in the first ballot of an election or selection 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_69e0b50192308190a284fcc89dd23a49 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e6fc3fdf3c8190abd3db7f5eb503a0 |
completed | April 21, 2026, 4:25 a.m. |
| PD | Predicate disambiguation | batch_69e5dbf274ac81909bbf245627dc8fdc |
completed | April 20, 2026, 7:55 a.m. |
Created at: April 16, 2026, 1:53 p.m.