Triple
T28291542
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2019 Afghan presidential election |
E713439
|
entity |
| Predicate | registeredVotersApprox |
P128148
|
FINISHED |
| Object | 9.6 million |
—
|
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: 9.6 million | Statement: [2019 Afghan presidential election, registeredVotersApprox, 9.6 million]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: registeredVotersApprox Context triple: [2019 Afghan presidential election, registeredVotersApprox, 9.6 million]
-
A.
votingPopulation
chosen
Indicates that the subject entity has a population of individuals who are eligible and/or registered to vote in elections associated with the object entity.
-
B.
numberOfVoters
Indicates the total count of individuals who participated in a particular vote or election.
-
C.
approximateNumberOfVotersBefore
Indicates that one value represents an estimated count of voters that existed prior to a specified point in time or event.
-
D.
eligibleVoters
Indicates that the referenced entities are legally permitted and qualified to vote in a given election or jurisdiction.
-
E.
hasVotingAgePopulation
Indicates that an entity has a specified number or set of people who are of legal voting age within its population.
- 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_69efb52371d88190a1381c4e58a3b731 |
completed | April 27, 2026, 7:12 p.m. |
| NER | Named-entity recognition | batch_69f64e37f7fc819083809149b6661e3c |
completed | May 2, 2026, 7:19 p.m. |
| PD | Predicate disambiguation | batch_69f64caede108190a35cc7cbfead866f |
completed | May 2, 2026, 7:12 p.m. |
Created at: April 27, 2026, 11:29 p.m.