Triple
T9519180
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lorne Greene |
E229602
|
entity |
| Predicate | employer |
P7
|
FINISHED |
| Object | NBC |
E2196
|
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: NBC | Statement: [Lorne Greene, employer, NBC]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: NBC Context triple: [Lorne Greene, employer, NBC]
-
A.
NBC
chosen
NBC is a major American broadcast television network known for its nationwide programming, including news, sports, and entertainment.
-
B.
NBC
NBC is a major westward-flowing ocean current along the northern coast of Brazil that transports warm water from the equatorial Atlantic toward the Caribbean.
-
C.
NBC USA
NBC USA is a major African American Christian denomination in the United States, formally known as the National Baptist Convention, USA, Inc.
-
D.
CBS
CBS is a leading Danish university in Copenhagen specializing in business and economics education and research.
-
E.
CBS
CBS is a major American broadcast television network known for airing a wide range of popular news, sports, and entertainment programming nationwide.
- 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_69ca847870a881909d8d751a7d29da39 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd9881e0f081909a0177cedc2e8b95 |
completed | April 1, 2026, 10:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d139ece5bc81908956e1f7ecbb1aa4 |
completed | April 4, 2026, 4:18 p.m. |
Created at: March 30, 2026, 7:59 p.m.