Triple
T3298229
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Critics' Choice Television Award |
E69267
|
entity |
| Predicate | formatCoverage |
P47833
|
FINISHED |
| Object | broadcast television |
—
|
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: broadcast television | Statement: [Critics' Choice Television Award, formatCoverage, broadcast television]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: formatCoverage Context triple: [Critics' Choice Television Award, formatCoverage, broadcast television]
-
A.
coverageScope
Indicates the extent or range of entities, conditions, or situations that are included under a particular coverage or applicability.
-
B.
hasCoverage
Indicates that one entity provides insurance or protection coverage for another entity or subject.
-
C.
providesCoverage
Indicates that one entity supplies protection, insurance, or service coverage to another entity or for a specified risk or scope.
-
D.
mapCoverage
Indicates the extent or area that is represented, covered, or included by a particular map.
-
E.
dataCoverage
Indicates the extent or proportion of relevant data that is included, captured, or represented within a given dataset or system.
- F. None of above. chosen
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_69ad859e529c8190a404273f53cb487d |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb0a2f4708190821edb9700f62d2f |
completed | March 8, 2026, 5:23 p.m. |
| PD | Predicate disambiguation | batch_69ada42407dc81909f60d7a14e1b7934 |
completed | March 8, 2026, 4:30 p.m. |
| PDg | Predicate description generation | batch_69ada526764881908e4bd52938d5374d |
completed | March 8, 2026, 4:34 p.m. |
Created at: March 8, 2026, 3:10 p.m.