Triple
T35853866
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | U.S. Census of Kentucky counties |
E1036441
|
entity |
| Predicate | dataQualityMeasures |
P91772
|
FINISHED |
| Object | address canvassing |
—
|
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: address canvassing | Statement: [U.S. Census of Kentucky counties, dataQualityMeasures, address canvassing]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: dataQualityMeasures Context triple: [U.S. Census of Kentucky counties, dataQualityMeasures, address canvassing]
-
A.
dataQuality
chosen
Indicates that one entity assesses or characterizes the quality, accuracy, or reliability of data associated with another entity.
-
B.
dataQualityNote
Indicates that there is a note or comment describing issues, assessments, or other information about the quality of the associated data.
-
C.
statisticMeasured
Indicates that a particular statistic or quantitative measure is obtained from, or used to evaluate, a given entity or phenomenon.
-
D.
dataReportedAs
Indicates that specific information has been communicated or recorded in a particular stated form, value, or representation.
-
E.
dataStandard
Indicates that there is a defined, agreed-upon specification or convention governing how the related data is structured, formatted, or exchanged.
- 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_69f76e1b4aa481909630373171eb5ec6 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7aa3883d48190b05e3d2da7a017ae |
completed | May 3, 2026, 8:04 p.m. |
| PD | Predicate disambiguation | batch_69f7a8d435288190b30b1991fb003121 |
completed | May 3, 2026, 7:58 p.m. |
Created at: May 3, 2026, 4:06 p.m.