Triple
T13192974
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lucien de Rubempré |
E314038
|
entity |
| Predicate | associatedWith |
P37
|
FINISHED |
| Object | Daniel d’Arthez |
E1350356
|
NE FINISHED |
How this triple was built (2 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: Daniel d’Arthez | Statement: [Lucien de Rubempré, associatedWith, Daniel d’Arthez]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Daniel d’Arthez Context triple: [Lucien de Rubempré, associatedWith, Daniel d’Arthez]
-
A.
Frédéric Arnault
Frédéric Arnault is a French business executive known for his leadership roles within the LVMH luxury group, particularly in its watch division.
-
B.
Louis Ducruet
Louis Ducruet is a Monegasque businessman and member of the Princely Family of Monaco, known as the son of Princess Stéphanie and for his work in sports management and royal engagements.
-
C.
Sébastien Auzière
Sébastien Auzière is a French financial analyst known publicly as the eldest son of Brigitte Macron, the First Lady of France.
-
D.
Félix Gaudissart
chosen
Félix Gaudissart is a fictional, fast-talking traveling salesman famed for his comic eloquence and blunders in Honoré de Balzac’s literature.
-
E.
Ernest Cossart
Ernest Cossart was a British-born character actor known for his numerous supporting roles in Hollywood films of the 1930s and 1940s.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d806ae1e08819090d95bfe1538cc17 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98c6158e4819082c8ad75b4dfdd90 |
completed | April 10, 2026, 11:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a05e64fe7408190914a43f7c44872d7 |
completed | May 14, 2026, 3:12 p.m. |
Created at: April 9, 2026, 9:16 p.m.