Triple
T21962497
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anna Geislerová |
E542366
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Geislerová |
—
|
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: Geislerová | Statement: [Anna Geislerová, familyName, Geislerová]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Geislerová Context triple: [Anna Geislerová, familyName, Geislerová]
-
A.
Anna Geislerová
chosen
Anna Geislerová is a prominent Czech film and television actress known for her acclaimed performances in both domestic and international productions.
-
B.
Lindauerová
Lindauerová is a Czech feminine surname form derived from the family name Lindauer.
-
C.
Metzgerová
Metzgerová is the Czech or Slovak feminine form of the surname Metzger.
-
D.
Fischerová
Fischerová is a Czech feminine surname derived from the German surname Fischer, commonly borne by women in Czech-speaking regions.
-
E.
Beránková
Beránková is the feminine form of the Czech surname Beránek, commonly used by women in Czech-speaking regions.
- 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_69e0c47fab1081908dc74a6545dbb051 |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f124572738819098cc669aafa53cc6 |
completed | April 28, 2026, 9:19 p.m. |
Created at: April 16, 2026, 8:01 p.m.