Triple
T1718079
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ext2 |
E37332
|
entity |
| Predicate | developer |
P73
|
FINISHED |
| Object |
Rémy Card
Rémy Card is a French software engineer best known for designing and implementing the ext2 filesystem for the Linux kernel.
|
E193766
|
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: Rémy Card | Statement: [ext2, developer, Rémy Card]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rémy Card Context triple: [ext2, developer, Rémy Card]
-
A.
Decléor
Decléor is a French skincare brand renowned for its use of aromatherapy and essential oils in professional-grade facial and body treatments.
-
B.
Vivant Denon
Vivant Denon was a French diplomat, writer, artist, and pioneering museum director best known for helping to create and lead the Louvre Museum after the French Revolution.
-
C.
Albert Cavos
Albert Cavos was a 19th-century Russian architect best known for designing major imperial theaters, including the Mariinsky Theatre in Saint Petersburg.
-
D.
Nissart
Nissart is a regional variety of the Occitan language traditionally spoken in and around the city of Nice in southeastern France.
-
E.
André
André is a given name of French origin commonly used in various languages as a form of "Andrew."
- 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: Rémy Card Triple: [ext2, developer, Rémy Card]
Generated description
Rémy Card is a French software engineer best known for designing and implementing the ext2 filesystem for the Linux kernel.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Rémy Card Target entity description: Rémy Card is a French software engineer best known for designing and implementing the ext2 filesystem for the Linux kernel.
-
A.
Decléor
Decléor is a French skincare brand renowned for its use of aromatherapy and essential oils in professional-grade facial and body treatments.
-
B.
Vivant Denon
Vivant Denon was a French diplomat, writer, artist, and pioneering museum director best known for helping to create and lead the Louvre Museum after the French Revolution.
-
C.
Albert Cavos
Albert Cavos was a 19th-century Russian architect best known for designing major imperial theaters, including the Mariinsky Theatre in Saint Petersburg.
-
D.
Nissart
Nissart is a regional variety of the Occitan language traditionally spoken in and around the city of Nice in southeastern France.
-
E.
André
André is a given name of French origin commonly used in various languages as a form of "Andrew."
- 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_69a8861912dc8190931af43b4b9158a7 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69aa6337d8408190bdba8b50652d50ae |
completed | March 6, 2026, 5:16 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad8ae6940c81909c1ebdfb0cdef5fc |
completed | March 8, 2026, 2:42 p.m. |
| NEDg | Description generation | batch_69ad957bd63c819099a508ca5c4102cc |
completed | March 8, 2026, 3:27 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ad97b18f9c8190a9c5ed80b5ed0195 |
completed | March 8, 2026, 3:37 p.m. |
Created at: March 4, 2026, 7:30 p.m.