Triple
T14847686
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Christopher Challis |
E349141
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Christopher Challis |
E349141
|
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: Christopher Challis | Statement: [Christopher Challis, name, Christopher Challis]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Christopher Challis Context triple: [Christopher Challis, name, Christopher Challis]
-
A.
Christopher Challis
chosen
Christopher Challis was a prominent British cinematographer known for his work on numerous classic films from the mid-20th century, often praised for his versatile and visually expressive style.
-
B.
Chris Grigg
Chris Grigg is a composer best known for his work on the music and sound design for the classic adventure game Maniac Mansion.
-
C.
Jeffrey Stott
Jeffrey Stott is a film producer best known for his work on the political comedy film "The American President."
-
D.
Christopher Gill
Christopher Gill is the charming yet psychopathic serial killer and master of disguise who serves as the central antagonist in the darkly comic thriller "No Way to Treat a Lady."
-
E.
Nick Campbell
Nick Campbell is a middle-aged, out-of-work salesman who becomes a tech company intern alongside his friend in the comedy film "The Internship."
- 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_69d822ec69008190a9232caa68836872 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69ded29236dc8190b7d3a37d09f9fb21 |
completed | April 14, 2026, 11:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe8bc9db7c8190af08b26471d28e97 |
completed | May 9, 2026, 1:20 a.m. |
Created at: April 10, 2026, 1:53 a.m.