Triple
T35020444
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Wichita Eagle |
E1010177
|
entity |
| Predicate | coverageEmphasis |
P192521
|
FINISHED |
| Object | local news coverage |
—
|
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: local news coverage | Statement: [The Wichita Eagle, coverageEmphasis, local news coverage]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: coverageEmphasis Context triple: [The Wichita Eagle, coverageEmphasis, local news coverage]
-
A.
coverageBasis
Indicates the underlying principle, rule, or criteria on which a particular coverage or protection is determined or applied.
-
B.
cobertura
Indicates that one entity provides coverage, protection, or a covering layer over another entity.
-
C.
edgeCoverage
Indicates that one element (such as a test, path, or configuration) covers or exercises a specific edge or connection in a graph or network structure.
-
D.
coverageModel
Indicates a relationship where a specific model or framework defines, structures, or governs the extent and manner in which something is covered or addressed.
-
E.
coverageScope
Indicates the extent or range of entities, conditions, or situations that are included under a particular coverage or applicability.
- 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_69f76dcc3ac8819096a3ed52f5fa2523 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69fd0d0ba5c48190bddb3f0e6637544c |
completed | May 7, 2026, 10:07 p.m. |
| PD | Predicate disambiguation | batch_69fd0c4324a8819086c90adf46216e0e |
completed | May 7, 2026, 10:03 p.m. |
| PDg | Predicate description generation | batch_69fd0d0aebac8190868a7714ddb4f1fd |
completed | May 7, 2026, 10:07 p.m. |
Created at: May 3, 2026, 4:01 p.m.