Triple
T13257275
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Howard Cosell |
E315690
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Cosell |
E315690
|
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: Cosell | Statement: [Howard Cosell, familyName, Cosell]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cosell Context triple: [Howard Cosell, familyName, Cosell]
-
A.
Cosell
chosen
Cosell is the surname of Howard Cosell, the influential and outspoken American sports journalist and broadcaster best known for his work on Monday Night Football.
-
B.
Cohon
Cohon is the family surname of American actor, author, and narrator Peter Coyote, born Peter Cohon.
-
C.
Cosey
Cosey is a surname most notably associated with the character Bill Cosey from Toni Morrison’s novel "Love."
-
D.
Honi Coles
Honi Coles was an acclaimed American tap dancer and choreographer renowned for his elegance, speed, and precision, and for helping to preserve and advance the jazz tap tradition.
-
E.
Sossick
Sossick is a Nigerian music producer known for crafting influential hip-hop and Afrobeats tracks for prominent artists.
- 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_69d806b1d9ac8190852c5571d5bd5f0f |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98f7614fc8190a1cac076d706e9aa |
completed | April 11, 2026, 12:01 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f70a4240d881909f0ee898fd272826 |
completed | May 3, 2026, 8:41 a.m. |
Created at: April 9, 2026, 9:25 p.m.