Triple
T32484935
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CBS News New York |
E830210
|
entity |
| Predicate | hasCoverageOf |
P60450
|
FINISHED |
| Object | New York City government |
E5244
|
NE 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: New York City government | Statement: [CBS News New York, hasCoverageOf, New York City government]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCoverageOf Context triple: [CBS News New York, hasCoverageOf, New York City government]
-
A.
hasCoverage
Indicates that one entity provides insurance or protection coverage for another entity or subject.
-
B.
isCoveredIn
Indicates that one entity has its surface or area overlaid, coated, or blanketed by another substance or material.
-
C.
providesCoverage
Indicates that one entity supplies protection, insurance, or service coverage to another entity or for a specified risk or scope.
-
D.
hasCoverageFocus
chosen
Indicates that one entity’s coverage, attention, or analysis is specifically focused on or directed toward another entity.
-
E.
hasBeenCoveredBy
Indicates that something has received coverage or treatment by another entity, such as being reported on, discussed, or addressed.
- F. None of above.
Provenance (4 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_69f34920aa4081908d8fb0277414b911 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_6a037c894b488190bcbec2eccaff4a01 |
completed | May 12, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a3466a452588190b901f41613899807 |
completed | June 18, 2026, 9:44 p.m. |
| PD | Predicate disambiguation | batch_6a0379edf2d88190b492fca86ed23cac |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 1, 2026, 12:58 a.m.