Triple
T21211114
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Captain William Diel |
E522720
|
entity |
| Predicate | hasColleague |
P398
|
FINISHED |
| Object | Chief Inspector Lee |
—
|
NE NERFINISHED |
How this triple was built (3 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: Chief Inspector Lee | Statement: [Captain William Diel, hasColleague, Chief Inspector Lee]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Chief Inspector Lee Context triple: [Captain William Diel, hasColleague, Chief Inspector Lee]
-
A.
Inspector Lee
Inspector Lee is a fictional alter-ego of author William S. Burroughs who appears as a hardboiled, hallucinatory detective figure in his experimental novel "The Soft Machine."
-
B.
Inspector Lee
Inspector Lee is a highly skilled and stoic Hong Kong police detective portrayed by Jackie Chan in the action-comedy Rush Hour film series.
-
C.
Detective Inspector Gaskill
Detective Inspector Gaskill is a police investigator character in the stage adaptation of "The Girl on the Train," responsible for probing the central mystery of the story.
-
D.
Detective John Kimble
Detective John Kimble is the tough undercover cop, played by Arnold Schwarzenegger, who poses as a kindergarten teacher in the action-comedy film "Kindergarten Cop."
-
E.
Chief Inspector Hubbard
Chief Inspector Hubbard is the shrewd, methodical Scotland Yard detective who unravels the murder plot in Alfred Hitchcock’s film "Dial M for Murder."
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Chief Inspector Lee Target entity description: Chief Inspector Lee is a skilled Hong Kong police detective and martial artist best known as Jackie Chan’s character in the Rush Hour film series.
-
A.
Inspector Lee
Inspector Lee is a fictional alter-ego of author William S. Burroughs who appears as a hardboiled, hallucinatory detective figure in his experimental novel "The Soft Machine."
-
B.
Inspector Lee
chosen
Inspector Lee is a highly skilled and stoic Hong Kong police detective portrayed by Jackie Chan in the action-comedy Rush Hour film series.
-
C.
Detective Inspector Gaskill
Detective Inspector Gaskill is a police investigator character in the stage adaptation of "The Girl on the Train," responsible for probing the central mystery of the story.
-
D.
Detective John Kimble
Detective John Kimble is the tough undercover cop, played by Arnold Schwarzenegger, who poses as a kindergarten teacher in the action-comedy film "Kindergarten Cop."
-
E.
Chief Inspector Hubbard
Chief Inspector Hubbard is the shrewd, methodical Scotland Yard detective who unravels the murder plot in Alfred Hitchcock’s film "Dial M for Murder."
- F. None of above.
Provenance (2 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_69e0b5112d8881909510b2dcdc93106d |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e7346eb20c8190aeb3c0cc0a24aaf9 |
completed | April 21, 2026, 8:25 a.m. |
Created at: April 16, 2026, 3:37 p.m.