Triple
T562512
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jay Leno |
E13481
|
entity |
| Predicate | employer |
P7
|
FINISHED |
| Object | CNBC |
E65797
|
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: CNBC | Statement: [Jay Leno, employer, CNBC]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: CNBC Context triple: [Jay Leno, employer, CNBC]
-
A.
CNBC
chosen
CNBC is an American business news television channel known for its real-time financial market coverage and economic analysis.
-
B.
CNN
CNN is a major American cable news television channel known for pioneering 24-hour news coverage and live reporting from global events.
-
C.
Fox Business Network
Fox Business Network is an American cable television channel focused on business and financial news, operated by Fox News Media.
-
D.
The Wall Street Journal
The Wall Street Journal is a leading American business-focused daily newspaper known for its influential financial reporting and analysis.
-
E.
NBC
NBC is a major American broadcast television network known for its nationwide programming, including news, sports, and entertainment.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69a4933edcf08190b35ecfd6014caee6 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49a700e608190b235246df057bd9b |
completed | March 1, 2026, 7:58 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a4ed37a98081909afbc0de4079dda8 |
completed | March 2, 2026, 1:51 a.m. |
Created at: March 1, 2026, 7:32 p.m.