Triple
T16435190
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ned Glass |
E399163
|
entity |
| Predicate | appearedIn |
P795
|
FINISHED |
| Object | Get Smart |
E574346
|
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: Get Smart | Statement: [Ned Glass, appearedIn, Get Smart]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Get Smart Context triple: [Ned Glass, appearedIn, Get Smart]
-
A.
Get Smart
Get Smart is a 2008 action-comedy film adaptation of the classic TV series, starring Steve Carell as an inept secret agent alongside Anne Hathaway.
-
B.
Pretty Smart
Pretty Smart is a Netflix comedy series following a high-strung, intellectual woman who moves in with her carefree sister and her quirky roommates, starring Emily Osment.
-
C.
Smart Ass
Smart Ass is a popular medium-roast coffee blend by Kicking Horse Coffee known for its bright, sweet, and chocolaty flavor profile.
-
D.
Get Smart (TV series)
chosen
Get Smart (TV series) is a 1960s American spy-fi comedy television show that parodies the secret agent genre through the misadventures of bumbling secret agent Maxwell Smart and his colleagues at the fictional CONTROL agency.
-
E.
Smart People
Smart People is a 2008 comedy-drama film about a widowed, self-absorbed literature professor whose life is upended by unexpected family and romantic developments.
- 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_69d87f2c6778819080fcfae53be8f12a |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e32ba1023481909588aa6a3c677886 |
completed | April 18, 2026, 6:58 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a004f4971e08190821d6b5aeed05624 |
completed | May 10, 2026, 9:26 a.m. |
Created at: April 10, 2026, 5:10 a.m.