Triple
T17340311
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stolen Kisses |
E421048
|
entity |
| Predicate | cinematographyBy |
P1953
|
FINISHED |
| Object |
Denis Clair
Denis Clair was a French cinematographer known for his work on François Truffaut’s film "Stolen Kisses."
|
E1262377
|
NE FINISHED |
How this triple was built (4 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: Denis Clair | Statement: [Stolen Kisses, cinematographyBy, Denis Clair]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Denis Clair Context triple: [Stolen Kisses, cinematographyBy, Denis Clair]
-
A.
Douglas Gerrard
Douglas Gerrard was an early 20th-century film actor and director who appeared in numerous silent-era productions.
-
B.
Michael Aldrich
Michael Aldrich was a British inventor and entrepreneur best known for pioneering online shopping and developing one of the first systems to connect consumers to businesses via a domestic television and telephone line.
-
C.
Hal Gibney
Hal Gibney was an American radio and television announcer best known for his work on the crime drama series "Dragnet."
-
D.
Lee Thompson
Lee Thompson is a British saxophonist and songwriter best known as a founding member of the ska band Madness.
-
E.
Justin Moorhouse
Justin Moorhouse is an English stand-up comedian and actor best known for his work on the sitcom "Phoenix Nights" and his appearances on British radio and television comedy shows.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Denis Clair Triple: [Stolen Kisses, cinematographyBy, Denis Clair]
Generated description
Denis Clair was a French cinematographer known for his work on François Truffaut’s film "Stolen Kisses."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Denis Clair Target entity description: Denis Clair was a French cinematographer known for his work on François Truffaut’s film "Stolen Kisses."
-
A.
Douglas Gerrard
Douglas Gerrard was an early 20th-century film actor and director who appeared in numerous silent-era productions.
-
B.
Michael Aldrich
Michael Aldrich was a British inventor and entrepreneur best known for pioneering online shopping and developing one of the first systems to connect consumers to businesses via a domestic television and telephone line.
-
C.
Hal Gibney
Hal Gibney was an American radio and television announcer best known for his work on the crime drama series "Dragnet."
-
D.
Lee Thompson
Lee Thompson is a British saxophonist and songwriter best known as a founding member of the ska band Madness.
-
E.
Justin Moorhouse
Justin Moorhouse is an English stand-up comedian and actor best known for his work on the sitcom "Phoenix Nights" and his appearances on British radio and television comedy shows.
- F. None of above. chosen
Provenance (5 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_69d889d3adc881909319f1edb8d2a956 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e43a14ec90819098db2ac0d58a53e1 |
completed | April 19, 2026, 2:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a018c588a7081909ab108cb4adfedfe |
completed | May 11, 2026, 7:59 a.m. |
| NEDg | Description generation | batch_6a018e0f09c881909296656b2732bf1e |
completed | May 11, 2026, 8:06 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a018e7b453c81909f75593237bcf9ec |
completed | May 11, 2026, 8:08 a.m. |
Created at: April 10, 2026, 5:44 a.m.