Triple
T33837712
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Apportionment Act of 1911 |
E867279
|
entity |
| Predicate | setNumberOfRepresentatives |
P4273
|
FINISHED |
| Object | 435 |
—
|
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: 435 | Statement: [Apportionment Act of 1911, setNumberOfRepresentatives, 435]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: setNumberOfRepresentatives Context triple: [Apportionment Act of 1911, setNumberOfRepresentatives, 435]
-
A.
setsMinimumNumberOfElectors
Indicates that an entity establishes or specifies the lowest allowable number of electors required in a given electoral context.
-
B.
numberOfRepresentatives
chosen
Indicates the quantity of representatives associated with a given entity or unit.
-
C.
numberOfColoniesRepresented
Indicates the count of distinct colonies that are represented or involved in relation to a given entity or context.
-
D.
increasedNumberOfElectors
Indicates that the number of electors associated with an entity has grown compared to a previous state or reference point.
-
E.
shareFederalRepresentation
Indicates that two or more entities are represented by the same federal-level representative or body within a governmental system.
- 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_69f34992ad40819087760ed939bd2a7a |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f7004cb70c8190863d6adc34904521 |
completed | May 3, 2026, 7:59 a.m. |
| PD | Predicate disambiguation | batch_69f6fc59518081908b0275f47721d561 |
completed | May 3, 2026, 7:42 a.m. |
Created at: May 1, 2026, 1:47 a.m.