Triple
T20518416
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arthur Kane |
E503739
|
entity |
| Predicate | birthName |
P65
|
FINISHED |
| Object | Arthur Harold Kane Jr. |
—
|
NE NERFINISHED |
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: Arthur Harold Kane Jr. | Statement: [Arthur Kane, birthName, Arthur Harold Kane Jr.]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Arthur Harold Kane Jr. Context triple: [Arthur Kane, birthName, Arthur Harold Kane Jr.]
-
A.
Arthur Kane
chosen
Arthur Kane was an American bassist best known as a co-founder of the influential proto-punk band the New York Dolls.
-
B.
Orlando Murden
Orlando Murden was an American songwriter best known for co-writing the classic soul ballad "For Once in My Life."
-
C.
Lew Harvey
Lew Harvey was an American character actor active during the early 20th century, appearing in numerous silent and early sound films.
-
D.
Gary Starkweather
Gary Starkweather was an American engineer and inventor best known for creating the laser printer while working at Xerox.
-
E.
George Kane
George Kane is a film and television producer known for his work on the Irish horror-comedy "Boys from County Hell."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69e0b4b2aa788190ae9eb37c1d73b1f1 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e69f43e0b08190b043f35645b264a0 |
completed | April 20, 2026, 9:48 p.m. |
Created at: April 16, 2026, 11:36 a.m.