Triple
T15357634
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Octan Corporation |
E367202
|
entity |
| Predicate | employs |
P7
|
FINISHED |
| Object | Good Cop |
E74788
|
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: Good Cop | Statement: [Octan Corporation, employs, Good Cop]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Good Cop Context triple: [Octan Corporation, employs, Good Cop]
-
A.
The Good Cop
The Good Cop is a 2018 Netflix comedy-drama series about an odd-couple father-son duo of NYPD detectives, created by veteran TV writer and producer Lowell Ganz.
-
B.
One Good Cop
One Good Cop is a 1991 crime drama film starring Michael Keaton as a New York City detective who must balance his dangerous job with caring for his late partner’s three young daughters.
-
C.
Bad Cop
chosen
Bad Cop is a central antagonist-turned-ally in *The Lego Movie*, depicted as a conflicted Lego police officer with a split good cop/bad cop personality.
-
D.
Bon Cop, Bad Cop
Bon Cop, Bad Cop is a bilingual Canadian action-comedy film that pairs an Ontario and a Quebec police officer who must overcome cultural differences to solve a cross-border crime.
-
E.
Cops
Cops is a long-running American reality television series that follows police officers on duty as they respond to real-life incidents and arrests.
- 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_69d85a1483788190ad93c2748e8af34b |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03e2d4934819097fc63603964217c |
completed | April 16, 2026, 1:41 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff0b45e3048190a7fa62ead6916fed |
completed | May 9, 2026, 10:24 a.m. |
Created at: April 10, 2026, 3:18 a.m.