Triple
T20166784
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dan Pfeiffer |
E491842
|
entity |
| Predicate | employer |
P7
|
FINISHED |
| Object | Crooked Media |
—
|
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: Crooked Media | Statement: [Dan Pfeiffer, employer, Crooked Media]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Crooked Media Context triple: [Dan Pfeiffer, employer, Crooked Media]
-
A.
Crooked Media
chosen
Crooked Media is a progressive American media company and podcast network known for political commentary shows like "Pod Save America."
-
B.
Vice Media
Vice Media is a digital media and broadcasting company known for its youth-oriented news, culture, and lifestyle content across online, television, and print platforms.
-
C.
Breitbart News
Breitbart News is a far-right American news and opinion website known for its provocative, nationalist, and populist political coverage.
-
D.
Storied Media Group
Storied Media Group is a media and production company that develops and produces film and television projects, often adapting stories from journalism and other narrative sources.
-
E.
Relativity Media
Relativity Media is an American film and media company known for financing, producing, and distributing a wide range of Hollywood movies across various genres.
- 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_69da6266c6888190bc1a3ecf24814d34 |
completed | April 11, 2026, 3:01 p.m. |
| NER | Named-entity recognition | batch_69e66844e49081909b7e9ec2b65cc61d |
completed | April 20, 2026, 5:54 p.m. |
Created at: April 11, 2026, 11:35 p.m.