Triple
T13321973
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bow Wow |
E317336
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Like Mike |
E639879
|
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: Like Mike | Statement: [Bow Wow, notableWork, Like Mike]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Like Mike Context triple: [Bow Wow, notableWork, Like Mike]
-
A.
Like Mike
chosen
Like Mike is a 2002 family sports comedy film about an orphan who gains extraordinary basketball skills after wearing a pair of magical sneakers.
-
B.
Only One Mike
Only One Mike is a stand-up comedy special by American comedian Mike Epps, showcasing his observational humor and storytelling style.
-
C.
Vinsanity
Vinsanity is the famous nickname of NBA star Vince Carter, celebrated for his spectacular dunks and electrifying athleticism.
-
D.
The Mick
The Mick is an American sitcom that follows a brash, irresponsible woman who unexpectedly becomes the guardian of her wealthy sister’s spoiled children.
-
E.
Encino Man
Encino Man is a 1992 comedy film about two high school students who discover and befriend a frozen prehistoric caveman in suburban California.
- 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_69d806b4d62c81908d4ced1665414be5 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d9992ab83c8190982d9f54dff6919f |
completed | April 11, 2026, 12:43 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f716efc3908190890e969c40694771 |
completed | May 3, 2026, 9:35 a.m. |
Created at: April 9, 2026, 9:30 p.m.