Triple
T7416948
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Golic and Wingo |
E171152
|
entity |
| Predicate | basedOn |
P98
|
FINISHED |
| Object | Mike and Mike |
E171151
|
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: Mike and Mike | Statement: [Golic and Wingo, basedOn, Mike and Mike]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mike and Mike Context triple: [Golic and Wingo, basedOn, Mike and Mike]
-
A.
Mike and Mike
chosen
Mike and Mike was a popular ESPN Radio morning sports talk show co-hosted by Mike Greenberg and Mike Golic that blended sports analysis with humor and pop culture.
-
B.
MIKE
MIKE is a high-resolution optical spectrograph used on the Magellan Telescopes for detailed astronomical spectroscopy.
-
C.
Pat and Mike
Pat and Mike is a 1952 sports comedy film starring Katharine Hepburn and Spencer Tracy, known for its witty script and depiction of a female athlete challenging gender norms.
-
D.
Micheal
Micheal is a given name, typically a variant spelling of the more common name Michael.
-
E.
Michael’s
Michael’s is a national arts and crafts retail chain known for selling hobby supplies, home décor, and DIY project materials.
- 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_69c68a618bdc81908d8018edadecd1a4 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f2c7ae0c8190a8348d6223aeeecc |
completed | March 27, 2026, 9:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c81eed92888190bf9d11ab91378fa9 |
completed | March 28, 2026, 6:33 p.m. |
Created at: March 27, 2026, 3:11 p.m.