Triple
T21295275
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Klemens Maria Hofbauer |
E524903
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Klemens |
—
|
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: Klemens | Statement: [Klemens Maria Hofbauer, givenName, Klemens]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Klemens Context triple: [Klemens Maria Hofbauer, givenName, Klemens]
-
A.
Klemens
chosen
Klemens is a given name, primarily used in German-speaking and Central European countries, that corresponds to the Latin-derived name Clemens.
-
B.
Klemensker
Klemensker is a small village on the Danish island of Bornholm, known for its rural setting and traditional Danish countryside character.
-
C.
Ottmar
Ottmar is a German former football player and highly successful manager best known for leading Borussia Dortmund and Bayern Munich to numerous domestic and European titles.
-
D.
Karl Joseph
Karl Joseph was the given name of Archduke Charles Joseph of Austria, a Habsburg archduke of the 18th century.
-
E.
Charles Dagomer
Charles Dagomer was an 18th-century French artist and teacher known for instructing painter Jean-Baptiste Huet.
- 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_69e0b517e6748190850d6f6ddf323d69 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e73857784881908c3b8418a4c00c1e |
completed | April 21, 2026, 8:41 a.m. |
Created at: April 16, 2026, 4:04 p.m.