Triple
T19539693
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sara Braun |
E488862
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Braun |
—
|
NE NERFINISHED |
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: Braun | Statement: [Sara Braun, familyName, Braun]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Braun Context triple: [Sara Braun, familyName, Braun]
-
A.
Braun
chosen
Braun is a German surname most infamously associated with Eva Braun, the longtime companion and brief wife of Adolf Hitler.
-
B.
Braun-Pivet
Braun-Pivet is the surname of Yaël Braun-Pivet, a prominent French politician who has served as President of the National Assembly.
-
C.
Brandt
Brandt is the obsequious personal assistant to the wealthy Jeffrey Lebowski in the cult film "The Big Lebowski," often serving as a nervous intermediary between him and the Dude.
-
D.
Brandt
Brandt is a German surname borne by numerous notable individuals across fields such as politics, science, and the arts.
-
E.
Gilette
Gilette is a small French commune in the Alpes-Maritimes department of southeastern France, known for its hilltop setting overlooking the confluence of the Var and Estéron rivers.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8e8db5b6c8190984b61f91981f575 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e63871d00881909ed7371ae5577957 |
completed | April 20, 2026, 2:30 p.m. |
Created at: April 10, 2026, 1:41 p.m.