Triple
T7402817
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Libre (fragrance) |
E170789
|
entity |
| Predicate | perfumer |
P39615
|
FINISHED |
| Object |
Carlos Benaïm
Carlos Benaïm is a renowned master perfumer known for creating numerous influential designer and niche fragrances over several decades.
|
E661811
|
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: Carlos Benaïm | Statement: [Libre (fragrance), perfumer, Carlos Benaïm]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Carlos Benaïm Context triple: [Libre (fragrance), perfumer, Carlos Benaïm]
-
A.
Joseph Mazilier
Joseph Mazilier was a 19th-century French ballet dancer, choreographer, and ballet master known for creating several major Romantic ballets.
-
B.
Pierre Azaria
Pierre Azaria was a French entrepreneur best known for founding the telecommunications company Alcatel.
-
C.
Paul-André Meyer
Paul-André Meyer was a French mathematician renowned for his foundational contributions to probability theory and stochastic processes.
-
D.
Peter Biziou
Peter Biziou is a British cinematographer known for his work on films such as "Bugsy Malone" and the Oscar-winning "Mississippi Burning."
-
E.
Luc Teyssier
Luc Teyssier is a charming, roguish French thief who becomes the romantic lead opposite Meg Ryan’s character in the 1995 romantic comedy film "French Kiss."
- 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: Carlos Benaïm Triple: [Libre (fragrance), perfumer, Carlos Benaïm]
Generated description
Carlos Benaïm is a renowned master perfumer known for creating numerous influential designer and niche fragrances over several decades.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Carlos Benaïm Target entity description: Carlos Benaïm is a renowned master perfumer known for creating numerous influential designer and niche fragrances over several decades.
-
A.
Joseph Mazilier
Joseph Mazilier was a 19th-century French ballet dancer, choreographer, and ballet master known for creating several major Romantic ballets.
-
B.
Pierre Azaria
Pierre Azaria was a French entrepreneur best known for founding the telecommunications company Alcatel.
-
C.
Paul-André Meyer
Paul-André Meyer was a French mathematician renowned for his foundational contributions to probability theory and stochastic processes.
-
D.
Peter Biziou
Peter Biziou is a British cinematographer known for his work on films such as "Bugsy Malone" and the Oscar-winning "Mississippi Burning."
-
E.
Luc Teyssier
Luc Teyssier is a charming, roguish French thief who becomes the romantic lead opposite Meg Ryan’s character in the 1995 romantic comedy film "French Kiss."
- 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_69c68a6010108190925e5284de022660 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f26ea27c8190a55e0e0314b463d8 |
completed | March 27, 2026, 9:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c81110d7648190a8938db7061be454 |
completed | March 28, 2026, 5:34 p.m. |
| NEDg | Description generation | batch_69c812b0b534819095dd2ae63ca7b2d0 |
completed | March 28, 2026, 5:41 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c8147b3f3c8190ada85c9e37bf5e2b |
completed | March 28, 2026, 5:48 p.m. |
Created at: March 27, 2026, 3:10 p.m.