Triple
T22209103
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Simon Sechter |
E548893
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Simon Sechter |
—
|
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: Simon Sechter | Statement: [Simon Sechter, name, Simon Sechter]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Simon Sechter Context triple: [Simon Sechter, name, Simon Sechter]
-
A.
Simon Sechter
chosen
Simon Sechter was a 19th-century Austrian music theorist, composer, and influential teacher of counterpoint, best known for mentoring composers such as Anton Bruckner.
-
B.
Carl Hilpert
Carl Hilpert was a German Wehrmacht general during World War II who held several high-level commands on the Eastern Front.
-
C.
Simon Hartmann
Simon Hartmann is a German local politician who serves as the mayor of the town of Northeim in Lower Saxony.
-
D.
Stephan Eberharter
Stephan Eberharter is a retired Austrian alpine ski racer who became one of the world’s top competitors in the late 1990s and early 2000s, winning multiple World Cup titles and Olympic medals.
-
E.
Wolfgang Sattler
Wolfgang Sattler is a notable individual who shares the surname Sattler, recognized enough to be specifically identified as a bearer of that name.
- 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_69e11e3f7e04819089806d81d5ac431e |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f12b29eb808190ab8abaa1e0e354fa |
completed | April 28, 2026, 9:48 p.m. |
Created at: April 16, 2026, 8:36 p.m.