Triple
T10944528
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marguerite Duthuit |
E258559
|
entity |
| Predicate | associatedWith |
P37
|
FINISHED |
| Object | Georges Duthuit |
E1120874
|
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: Georges Duthuit | Statement: [Marguerite Duthuit, associatedWith, Georges Duthuit]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Georges Duthuit Context triple: [Marguerite Duthuit, associatedWith, Georges Duthuit]
-
A.
Georges Duthuit
chosen
Georges Duthuit was a French art critic and historian known for his close association with avant-garde artists and his influential writings on modern art.
-
B.
Pierre Montet
Pierre Montet was a French Egyptologist renowned for his excavations and discoveries in ancient Egyptian sites, particularly royal tombs.
-
C.
Pierre Lescure
Pierre Lescure is a French media executive and journalist best known as the co-founder and former CEO of the television network Canal+ and a prominent figure in France’s entertainment industry.
-
D.
Geraud Brisson
Geraud Brisson is a film editor known for his work on the movie "CODA."
-
E.
Francisque Duret
Francisque Duret was a 19th-century French sculptor known for his influential public monuments and contributions to academic sculpture in Paris.
- 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_69d6aa8769b4819082bfe5e61b9017f0 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d770c4d59481908a5900fc8cf9ecc3 |
completed | April 9, 2026, 9:26 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe387a261c8190a9ac11d6e4e7b29c |
completed | May 8, 2026, 7:24 p.m. |
Created at: April 8, 2026, 9:23 p.m.