Triple
T1975988
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2020 United States census |
E42912
|
entity |
| Predicate | apportionmentPopulation |
P328
|
FINISHED |
| Object | 331108434 |
—
|
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: 331108434 | Statement: [2020 United States census, apportionmentPopulation, 331108434]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: apportionmentPopulation Context triple: [2020 United States census, apportionmentPopulation, 331108434]
-
A.
apportionedBy
Indicates that something is divided or allocated among parts or recipients according to a specified agent, rule, or method.
-
B.
apportionmentUnit
Indicates a relationship where something (such as a resource, cost, or quantity) is divided or allocated according to a specified unit or basis of apportionment.
-
C.
apportionedAfter
Indicates that one entity is distributed, allocated, or divided only after another specified event, action, or allocation has occurred.
-
D.
numberOfRepresentatives
Indicates the quantity of representatives associated with a given entity or unit.
-
E.
population
chosen
Indicates the total number of individuals living in or present within a specified area or group.
- 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_69a8871289048190b00b0d7744b7b2b1 |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb3f835108190b0709ccf3a487a96 |
completed | March 7, 2026, 5:13 a.m. |
| PD | Predicate disambiguation | batch_69abaff9a09c8190a81fa13f4b85bc79 |
completed | March 7, 2026, 4:56 a.m. |
Created at: March 4, 2026, 7:36 p.m.