Triple
T17550809
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Franck Leroy |
E427456
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Franck
Franck is a masculine given name of French origin commonly used in Francophone countries.
|
E1274963
|
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: Franck | Statement: [Franck Leroy, givenName, Franck]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Franck Context triple: [Franck Leroy, givenName, Franck]
-
A.
Franck
Franck is a surname most notably associated with James Franck, the German physicist and Nobel laureate recognized for the Franck–Hertz experiment.
-
B.
Guy-Blaché
Guy-Blaché is the surname of pioneering French filmmaker Alice Guy-Blaché, one of the first female directors and early innovators in narrative cinema.
-
C.
Marcel Fournier
Marcel Fournier was a French businessman best known as a co-founder of the multinational retail corporation Carrefour, a pioneer of the modern hypermarket concept.
-
D.
Royer
Royer was a costume designer known for his work on classic Hollywood films, including the 1939 drama "The Rains Came."
-
E.
Franck Leroy
Franck Leroy is a French politician known for serving as the mayor of Épernay, a commune in the Marne department of northeastern France.
- 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: Franck Triple: [Franck Leroy, givenName, Franck]
Generated description
Franck is a masculine given name of French origin commonly used in Francophone countries.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Franck Target entity description: Franck is a masculine given name of French origin commonly used in Francophone countries.
-
A.
Franck
Franck is a surname most notably associated with James Franck, the German physicist and Nobel laureate recognized for the Franck–Hertz experiment.
-
B.
Guy-Blaché
Guy-Blaché is the surname of pioneering French filmmaker Alice Guy-Blaché, one of the first female directors and early innovators in narrative cinema.
-
C.
Marcel Fournier
Marcel Fournier was a French businessman best known as a co-founder of the multinational retail corporation Carrefour, a pioneer of the modern hypermarket concept.
-
D.
Royer
Royer was a costume designer known for his work on classic Hollywood films, including the 1939 drama "The Rains Came."
-
E.
Franck Leroy
Franck Leroy is a French politician known for serving as the mayor of Épernay, a commune in the Marne department of northeastern France.
- 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_69d889df6dc081908f67dbadc03c07ee |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e454656dc08190bba85b93bd07b0a2 |
completed | April 19, 2026, 4:04 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a01d290edbc8190a7b2cb0835456890 |
completed | May 11, 2026, 12:58 p.m. |
| NEDg | Description generation | batch_6a01d597c96c8190a5eca56a748da50c |
completed | May 11, 2026, 1:11 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a01d639c220819088dd3389d1ab60ca |
completed | May 11, 2026, 1:14 p.m. |
Created at: April 10, 2026, 5:50 a.m.