Triple
T1976004
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2020 United States census |
E42912
|
entity |
| Predicate | questionnaireLanguageSupport |
P11734
|
FINISHED |
| Object | English |
—
|
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: English | Statement: [2020 United States census, questionnaireLanguageSupport, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: questionnaireLanguageSupport Context triple: [2020 United States census, questionnaireLanguageSupport, English]
-
A.
languagesSpoken
Indicates that an entity is able to communicate using one or more specified languages.
-
B.
hasLanguageStatus
Indicates that an entity has a particular status or condition regarding its language use, recognition, or classification.
-
C.
languageProvision
chosen
Indicates that one entity supplies, supports, or makes available a particular language (or set of languages) for use by another entity.
-
D.
languageOfAssessment
Indicates that a specified language is used as the medium of assessment (e.g., for tests, evaluations, or examinations) for a given entity.
-
E.
includesLanguage
Indicates that one entity contains, supports, or makes use of a specified language as part of its content, functionality, or representation.
- 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.