Triple
T96235
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | congressional district method |
E1937
|
entity |
| Predicate | statewideElectorsCount |
P280
|
FINISHED |
| Object | 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: 2 | Statement: [congressional district method, statewideElectorsCount, 2]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: statewideElectorsCount Context triple: [congressional district method, statewideElectorsCount, 2]
-
A.
hasElectoralVotes
chosen
Indicates that a political entity (such as a state or district) possesses a specified number of votes in an electoral system used to choose an officeholder.
-
B.
electoralVotesNeededToWin
Indicates the minimum number of electoral votes a candidate must obtain in an election to be declared the winner.
-
C.
numberOfColoniesRepresented
Indicates the count of distinct colonies that are represented or involved in relation to a given entity or context.
-
D.
numberOfStates
Indicates the total count of distinct states or conditions associated with an entity or system.
-
E.
numberOfMemberStates
Indicates the total count of member states associated with a given entity or organization.
- 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_69a24d4862f881908cc8b89d3a78031d |
completed | Feb. 28, 2026, 2:04 a.m. |
| NER | Named-entity recognition | batch_69a250cb400c8190b56343bbe19b48c7 |
completed | Feb. 28, 2026, 2:19 a.m. |
| PD | Predicate disambiguation | batch_69a24ebd19c48190bab291fea0ecc0c2 |
completed | Feb. 28, 2026, 2:11 a.m. |
Created at: Feb. 28, 2026, 2:09 a.m.