Triple
T7386799
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Suter |
E170401
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Sauter |
E170402
|
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: Sauter | Statement: [Suter, hasVariant, Sauter]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sauter Context triple: [Suter, hasVariant, Sauter]
-
A.
Sauter
chosen
Sauter is a surname of German origin, often associated with individuals in fields such as music, engineering, and business.
-
B.
Sautter
Sautter is a surname, likely a spelling variant of "Sutter," borne by various individuals and families of European origin.
-
C.
Sauvy
Sauvy is a French surname most notably borne by Alfred Sauvy, a prominent demographer, sociologist, and economist.
-
D.
Drouet
Drouet is a French surname most notably associated with Jean-Baptiste Drouet, the postmaster who helped identify and arrest King Louis XVI during his attempted flight in 1791.
-
E.
Breuillet
Breuillet is a commune in the Essonne department in the Île-de-France region of northern France.
- 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_69c68a5e2c9081909e713ce866e0060a |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f1f2bac481908ac74069182a4ce4 |
completed | March 27, 2026, 9:09 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c802e56fb48190976612d2a94d6ee5 |
completed | March 28, 2026, 4:33 p.m. |
Created at: March 27, 2026, 3:08 p.m.