Triple
T11713412
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zouzou |
E278428
|
entity |
| Predicate | cinematographyBy |
P1953
|
FINISHED |
| Object |
Roger Hubert
Roger Hubert was a French cinematographer known for his work on mid-20th-century films, contributing to the visual style of classic French cinema.
|
E942066
|
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: Roger Hubert | Statement: [Zouzou, cinematographyBy, Roger Hubert]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Roger Hubert Context triple: [Zouzou, cinematographyBy, Roger Hubert]
-
A.
Thomas Hubert
Thomas Hubert is an author known for his work on the artificial intelligence program AlphaGo Zero.
-
B.
Rene Hubert
Rene Hubert was a Swiss-born Hollywood costume designer known for his elegant and historically detailed work on numerous classic films of the 1930s–1950s.
-
C.
Hubert
Hubert is a masculine given name of Germanic origin meaning "bright heart" or "shining intellect," historically borne by saints, nobles, and notable public figures.
-
D.
Hugh Lambert
Hugh Lambert was an American dancer and choreographer best known for his work in film and television musicals and for being married to singer Nancy Sinatra.
-
E.
Eddy Colbert
Eddy Colbert is an individual notable enough to be recognized as a namesake or prominent bearer of the surname Colbert.
- 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: Roger Hubert Triple: [Zouzou, cinematographyBy, Roger Hubert]
Generated description
Roger Hubert was a French cinematographer known for his work on mid-20th-century films, contributing to the visual style of classic French cinema.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Roger Hubert Target entity description: Roger Hubert was a French cinematographer known for his work on mid-20th-century films, contributing to the visual style of classic French cinema.
-
A.
Thomas Hubert
Thomas Hubert is an author known for his work on the artificial intelligence program AlphaGo Zero.
-
B.
Rene Hubert
Rene Hubert was a Swiss-born Hollywood costume designer known for his elegant and historically detailed work on numerous classic films of the 1930s–1950s.
-
C.
Hubert
Hubert is a masculine given name of Germanic origin meaning "bright heart" or "shining intellect," historically borne by saints, nobles, and notable public figures.
-
D.
Hugh Lambert
Hugh Lambert was an American dancer and choreographer best known for his work in film and television musicals and for being married to singer Nancy Sinatra.
-
E.
Eddy Colbert
Eddy Colbert is an individual notable enough to be recognized as a namesake or prominent bearer of the surname Colbert.
- 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_69d6aaff2ce88190b4a1e4b341ad5377 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a4be10088190854699385d1f6a95 |
completed | April 10, 2026, 7:20 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ef838562d08190b9a764e88c50d423 |
completed | April 27, 2026, 3:40 p.m. |
| NEDg | Description generation | batch_69ef9b68309081909f3f614efeeb2ab1 |
completed | April 27, 2026, 5:22 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69efd6aba82c81909ff22e6b26db3cfe |
completed | April 27, 2026, 9:35 p.m. |
Created at: April 8, 2026, 9:40 p.m.