Triple
T22480681
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Peggy Noonan |
E555754
|
entity |
| Predicate | employer |
P7
|
FINISHED |
| Object | CBS News |
—
|
NE NERFINISHED |
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: CBS News | Statement: [Peggy Noonan, employer, CBS News]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: CBS News Context triple: [Peggy Noonan, employer, CBS News]
-
A.
CBS News
chosen
CBS News is a major American television and digital news division known for producing national and international news programs and journalism for the CBS network.
-
B.
NBC News
NBC News is a major American television news division known for producing national and international news programs across broadcast and digital platforms.
-
C.
ABC News
ABC News is an Australian 24-hour news television channel providing national and international news coverage, analysis, and current affairs programming.
-
D.
ABC News
ABC News is the news division of the American Broadcasting Company, providing television, digital, and radio news coverage in the United States and internationally.
-
E.
NBC News Now
NBC News Now is a free, ad-supported streaming news channel from NBC News that provides live, rolling coverage and original news programming across digital platforms.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e11e53897c819088863779f8c50bb0 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15c3836a08190b6f0d88b94cb80a3 |
completed | April 29, 2026, 1:17 a.m. |
Created at: April 16, 2026, 8:49 p.m.