Triple
T364395
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Herbrand Award |
E7926
|
entity |
| Predicate | notableRecipient |
P108
|
FINISHED |
| Object |
Gérard Huet
Gérard Huet is a French computer scientist known for his influential work in formal methods, type theory, and the development of the Coq proof assistant.
|
E52376
|
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: Gérard Huet | Statement: [Herbrand Award, notableRecipient, Gérard Huet]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gérard Huet Context triple: [Herbrand Award, notableRecipient, Gérard Huet]
-
A.
Jean-Paul Agon
Jean-Paul Agon is a French business executive best known for serving as the longtime CEO and later chairman of global cosmetics giant L'Oréal.
-
B.
Jean-Luc Vaillant
Jean-Luc Vaillant is a French software engineer and entrepreneur best known as a co-founder and former chief technology officer of LinkedIn.
-
C.
Jean-François Soitoux
Jean-François Soitoux was a 19th-century French sculptor known for his academic style and for mentoring artists such as Frédéric Auguste Bartholdi.
-
D.
Émile Nouguier
Émile Nouguier was a French civil engineer best known as one of the principal designers of the Eiffel Tower.
-
E.
Robert Fraisse
Robert Fraisse is a French cinematographer known for his visually striking work on international films, including major war dramas and action features.
- 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: Gérard Huet Triple: [Herbrand Award, notableRecipient, Gérard Huet]
Generated description
Gérard Huet is a French computer scientist known for his influential work in formal methods, type theory, and the development of the Coq proof assistant.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Gérard Huet Target entity description: Gérard Huet is a French computer scientist known for his influential work in formal methods, type theory, and the development of the Coq proof assistant.
-
A.
Jean-Paul Agon
Jean-Paul Agon is a French business executive best known for serving as the longtime CEO and later chairman of global cosmetics giant L'Oréal.
-
B.
Jean-Luc Vaillant
Jean-Luc Vaillant is a French software engineer and entrepreneur best known as a co-founder and former chief technology officer of LinkedIn.
-
C.
Jean-François Soitoux
Jean-François Soitoux was a 19th-century French sculptor known for his academic style and for mentoring artists such as Frédéric Auguste Bartholdi.
-
D.
Émile Nouguier
Émile Nouguier was a French civil engineer best known as one of the principal designers of the Eiffel Tower.
-
E.
Robert Fraisse
Robert Fraisse is a French cinematographer known for his visually striking work on international films, including major war dramas and action features.
- 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_69a2e7e880008190a6ad7e06e5d03007 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ebe6c1b4819083335e880c205ed6 |
completed | Feb. 28, 2026, 1:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a41b44959c8190a793b4e5af838c7c |
completed | March 1, 2026, 10:56 a.m. |
| NEDg | Description generation | batch_69a41bd12bdc81909fc3da7e3a01642b |
completed | March 1, 2026, 10:58 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69a42290059481908d0b10769263b0da |
completed | March 1, 2026, 11:27 a.m. |
Created at: Feb. 28, 2026, 1:08 p.m.