Triple
T7040967
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Georges Cuvier |
E163508
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Cuvier |
E163508
|
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: Cuvier | Statement: [Georges Cuvier, familyName, Cuvier]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cuvier Context triple: [Georges Cuvier, familyName, Cuvier]
-
A.
Cuvier
chosen
Cuvier is the surname of Georges Cuvier, a pioneering French naturalist and zoologist regarded as the founder of comparative anatomy and paleontology.
-
B.
Cuvier Grover
Cuvier Grover was a Union Army general during the American Civil War, noted for his leadership in several major campaigns and battles.
-
C.
Gressier
Gressier is a coastal commune in western Haiti known for its proximity to Port-au-Prince and its vulnerability to earthquakes and hurricanes.
-
D.
Binoche
Binoche is the surname of Juliette Binoche, the acclaimed French actress known for her roles in films such as "The English Patient" and "Chocolat."
-
E.
Vuchetich
Vuchetich is a Russian surname most notably borne by Soviet sculptor Yevgeny Vuchetich, renowned for his monumental war memorials.
- 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_69c6885e7c1c8190be32a8f79ab4e0cf |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6e22544708190b0dffb5256d4cda6 |
completed | March 27, 2026, 8:01 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c775afabbc8190a6ff263b1a996c9c |
completed | March 28, 2026, 6:31 a.m. |
Created at: March 27, 2026, 2:36 p.m.