Triple
T9631955
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Katalin |
E232828
|
entity |
| Predicate | equivalentNameInGerman |
P22792
|
FINISHED |
| Object | Katharina |
E263534
|
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: Katharina | Statement: [Katalin, equivalentNameInGerman, Katharina]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Katharina Context triple: [Katalin, equivalentNameInGerman, Katharina]
-
A.
Katharina
chosen
Katharina is a feminine given name, commonly used in German-speaking and other European countries, that is a variant of Katherine/Catherine.
-
B.
Katherina
Katherina is the given first name of Katia Mann, the wife of German novelist Thomas Mann.
-
C.
Katherina
Katherina is the sharp-tongued, strong-willed heroine of Shakespeare’s comedy *The Taming of the Shrew*, whose fiery personality and contentious courtship drive the play’s central conflict.
-
D.
Verena
Verena is a feminine given name of Latin origin, commonly used in German-speaking and other European countries.
-
E.
Gertrudis
Gertrudis is a passionate and rebellious sister in "Like Water for Chocolate" whose fiery nature and unconventional choices challenge her family's strict traditions.
- 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_69ca848940cc8190b97cec654cb3bb4a |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd9b2783b48190a9929dc3e3cd2956 |
completed | April 1, 2026, 10:24 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1822e12b8819089d4a64a9980cfcd |
completed | April 4, 2026, 9:27 p.m. |
Created at: March 30, 2026, 8:11 p.m.