Triple
T22838483
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Words and Pictures |
E566010
|
entity |
| Predicate | editedBy |
P1954
|
FINISHED |
| Object | Peter Honess |
—
|
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: Peter Honess | Statement: [Words and Pictures, editedBy, Peter Honess]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Peter Honess Context triple: [Words and Pictures, editedBy, Peter Honess]
-
A.
Peter Honess
chosen
Peter Honess is a British film editor best known for his work on major Hollywood films, including the acclaimed neo-noir crime drama "L.A. Confidential."
-
B.
Peter Hirt
Peter Hirt is a Swiss racing driver known for competing in Formula One during the early 1950s.
-
C.
Don Peters
Don Peters is a character in Stephen King and Owen King's novel "Sleeping Beauties," involved in the unfolding crisis when women worldwide fall into a mysterious sleep.
-
D.
Paul Kohner
Paul Kohner was a prominent Hollywood talent agent and film producer who represented major European and American stars during the mid-20th century.
-
E.
Peter Borish
Peter Borish is an American investor, economist, and philanthropist best known as a founding partner of Tudor Investment Corporation and for his extensive work in charitable and public policy initiatives.
- 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_69e245869e188190a196584f36e682da |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17e8244dc819089c0a7525fb512ab |
completed | April 29, 2026, 3:44 a.m. |
Created at: April 17, 2026, 3:35 p.m.