Triple
T5848343
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dan Fouts |
E129766
|
entity |
| Predicate | broadcastingCareer |
P38564
|
FINISHED |
| Object | CBS Sports NFL analyst |
—
|
LITERAL 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: CBS Sports NFL analyst | Statement: [Dan Fouts, broadcastingCareer, CBS Sports NFL analyst]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: broadcastingCareer Context triple: [Dan Fouts, broadcastingCareer, CBS Sports NFL analyst]
-
A.
televisionAnnouncers
chosen
Indicates a relationship where certain people serve as announcers or presenters on television broadcasts.
-
B.
broadcastNetwork
Indicates that one entity serves as the television or radio network that broadcasts the programming or content of another entity.
-
C.
notableBroadcaster
Indicates that the subject is a broadcaster who is particularly prominent, influential, or widely recognized.
-
D.
sportsCareer
Indicates a relationship where an entity’s professional involvement, roles, or achievements in sports are associated with a particular sport, team, period, or competitive level.
-
E.
laterNetworkOfBroadcast
Indicates that one broadcast network succeeds or replaces another in time, coming into operation after the earlier network.
- F. None of above.
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_69c0084bd31c8190a796bb6284845e83 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c03c9239e08190bff7ef2bd6d21ae0 |
completed | March 22, 2026, 7:01 p.m. |
| PD | Predicate disambiguation | batch_69c0334412388190bc594794ec5754f9 |
completed | March 22, 2026, 6:21 p.m. |
Created at: March 22, 2026, 3:55 p.m.