Triple
T7855355
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Franziska Matzelsberger |
E182160
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Franziska |
E83113
|
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: Franziska | Statement: [Franziska Matzelsberger, givenName, Franziska]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Franziska Context triple: [Franziska Matzelsberger, givenName, Franziska]
-
A.
Franziska
chosen
Franziska is a feminine given name of German origin, closely related to and cognate with the name Frances.
-
B.
Verena
Verena is a feminine given name of Latin origin, commonly used in German-speaking and other European countries.
-
C.
Gisela
Gisela was a daughter of Charlemagne, the Frankish king and first Holy Roman Emperor, and a member of the Carolingian royal family.
-
D.
Elfriede
Elfriede is a feminine given name of German origin, notably borne by Austrian Nobel Prize–winning writer Elfriede Jelinek.
-
E.
Ottla
Ottla was the beloved younger sister of writer Franz Kafka, known from his diaries and letters for her close relationship with him and her tragic death in the Holocaust.
- 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_69ca82869ee08190b8f9040dbc2c0467 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb1a74592c8190b42f298e3e33617b |
completed | March 31, 2026, 12:51 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cb5b27e9b081909a0574458ddf43b0 |
completed | March 31, 2026, 5:27 a.m. |
Created at: March 30, 2026, 4:52 p.m.