Triple
T10148577
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nelly Roussel |
E231771
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Roussel |
E45966
|
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: Roussel | Statement: [Nelly Roussel, familyName, Roussel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Roussel Context triple: [Nelly Roussel, familyName, Roussel]
-
A.
Roussel
chosen
Roussel is a surname of French origin, often used as an alternative spelling of Russell.
-
B.
Rousselot
Rousselot is a French surname borne by various notable figures, including acclaimed cinematographer Philippe Rousselot.
-
C.
Rabaut Saint-Étienne
Rabaut Saint-Étienne was an 18th-century French Protestant pastor and revolutionary politician who played a significant role in advocating religious tolerance during the French Revolution.
-
D.
Charpentier
Charpentier is a French surname borne by various notable individuals across fields such as science, arts, and politics.
-
E.
Clairmarais
Clairmarais is a small commune in northern France known for its marshlands and canals, situated near the town of Saint-Omer.
- 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_69ca848364f881908a24366a6feec1db |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cdec024da481908b8170fcf3b18e67 |
completed | April 2, 2026, 4:09 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d3175fa0c0819088d372f534f9447e |
completed | April 6, 2026, 2:15 a.m. |
Created at: March 30, 2026, 9:08 p.m.