Triple
T31397601
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1940 United States census |
E800902
|
entity |
| Predicate | introducedQuestionOn |
P8259
|
FINISHED |
| Object | income |
—
|
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: income | Statement: [1940 United States census, introducedQuestionOn, income]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: introducedQuestionOn Context triple: [1940 United States census, introducedQuestionOn, income]
-
A.
introduced
Indicates that one entity caused another entity to become known, presented, or brought into use for the first time to a person, group, or context.
-
B.
introducedDuring
chosen
Indicates that one entity was first brought into existence, use, or awareness within the time period, event, or context specified by the other entity.
-
C.
introducedFor
Indicates that one entity was presented or brought to the attention of another entity for a specific purpose or role.
-
D.
oftenIntroducedBy
Indicates that one entity is frequently presented, mentioned, or brought into context by another entity.
-
E.
questionedSince
Indicates that one entity has been subject to questioning or inquiry by another entity starting from a specific point in time and continuing thereafter.
- 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_69f224ea9998819086ae2e4f4f4091c8 |
completed | April 29, 2026, 3:34 p.m. |
| NER | Named-entity recognition | batch_69fd32848ea88190a71e6df402bbb30e |
completed | May 8, 2026, 12:47 a.m. |
| PD | Predicate disambiguation | batch_69fd2d7e95588190991d5f21e25155df |
completed | May 8, 2026, 12:25 a.m. |
Created at: April 29, 2026, 9:19 p.m.