Triple
T12883559
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dr. Finkelstein |
E308163
|
entity |
| Predicate | voicedBy |
P2181
|
FINISHED |
| Object | William Hickey |
E308166
|
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: William Hickey | Statement: [Dr. Finkelstein, voicedBy, William Hickey]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: William Hickey Context triple: [Dr. Finkelstein, voicedBy, William Hickey]
-
A.
William Hickey
chosen
William Hickey was an American character actor known for his distinctive raspy voice and eccentric roles in film, television, and theater.
-
B.
Malcolm Byrne
Malcolm Byrne is a historian and analyst known for his work on U.S. foreign policy and declassified government documents, often in collaboration with fellow researcher Peter Kornbluh.
-
C.
John Hadden
John Hadden is a theater artist and director best known as a co-founder of the Shakespeare & Company theater troupe.
-
D.
Philip Giffin
Philip Giffin is a film and television composer known for his work on the series "Boomtown."
-
E.
Murray Slaughter
Murray Slaughter is a fictional television news writer best known as a central character on the classic sitcom "The Mary Tyler Moore Show."
- 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_69d7bdf7c1f0819098102569a8d8cbf5 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d970fd15888190baf90fc30f2a3e25 |
completed | April 10, 2026, 9:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6a5556fe081909ada9d491b21b17b |
completed | May 3, 2026, 1:31 a.m. |
Created at: April 9, 2026, 5:39 p.m.