Triple
T7140047
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Representation of the People Act 1918 |
E166417
|
entity |
| Predicate | approximateMenVotersAdded |
P75069
|
FINISHED |
| Object | about 5.2 million men |
—
|
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: about 5.2 million men | Statement: [Representation of the People Act 1918, approximateMenVotersAdded, about 5.2 million men]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: approximateMenVotersAdded Context triple: [Representation of the People Act 1918, approximateMenVotersAdded, about 5.2 million men]
-
A.
approximateNumberOfVotersBefore
Indicates that one value represents an estimated count of voters that existed prior to a specified point in time or event.
-
B.
numberOfVoters
Indicates the total count of individuals who participated in a particular vote or election.
-
C.
eligibleVoters
Indicates that the referenced entities are legally permitted and qualified to vote in a given election or jurisdiction.
-
D.
typicalAgeOfVoters
Indicates the usual or most common age range of individuals who participate as voters in elections or voting processes.
-
E.
voterTurnoutChange
Indicates the amount or direction of change in voter turnout between two elections or time periods.
- 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_69c6888579d481909e05a8d6b81bf733 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e7775e408190b880abde0a3f8d12 |
completed | March 27, 2026, 8:24 p.m. |
| PD | Predicate disambiguation | batch_69c6e1c932888190b125ca3785b18553 |
completed | March 27, 2026, 8 p.m. |
| PDg | Predicate description generation | batch_69c6e4a213508190a40aca39f9eee7d5 |
completed | March 27, 2026, 8:12 p.m. |
Created at: March 27, 2026, 2:45 p.m.