Triple
T1688571
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bettina |
E36497
|
entity |
| Predicate | hasRelatedName |
P3889
|
FINISHED |
| Object | Bettine |
E36497
|
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: Bettine | Statement: [Bettina, hasRelatedName, Bettine]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bettine Context triple: [Bettina, hasRelatedName, Bettine]
-
A.
Bettina
chosen
Bettina is a feminine given name of Hebrew origin, often considered a diminutive of Elisabeth or Benedetta and used in various European languages.
-
B.
Anna von Bönninghausen
Anna von Bönninghausen was a 17th-century German noblewoman best known as the mother of Bernhard von Galen, the influential Prince-Bishop of Münster.
-
C.
Constanze von Meyenburg
Constanze von Meyenburg was the wife of Swiss playwright and novelist Max Frisch.
-
D.
Dorothee
Dorothee is a feminine given name, commonly used in German- and French-speaking countries, that is a variant of the name Dorothea.
-
E.
Franziska
Franziska is a feminine given name of German origin, closely related to and cognate with the name Frances.
- 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_69a886151508819084fa7f1ce6e05577 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69aa6296655c8190835ec0d20f7460ca |
completed | March 6, 2026, 5:13 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad7992792081909af4312ae8a448a2 |
completed | March 8, 2026, 1:28 p.m. |
Created at: March 4, 2026, 7:29 p.m.