Triple
T6199647
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vávrová |
E138596
|
entity |
| Predicate | genderFormOf |
P17779
|
FINISHED |
| Object | Vávra |
E138596
|
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: Vávra | Statement: [Vávrová, genderFormOf, Vávra]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Vávra Context triple: [Vávrová, genderFormOf, Vávra]
-
A.
Vávrová
chosen
Vávrová is a Czech surname most notably borne by Dana Vávrová, a well-known Czech-German actress and film director.
-
B.
Váh
Váh is the longest river in Slovakia, flowing through much of the country before joining the Danube.
-
C.
Javorná
Javorná is a small river in the Czech Republic that serves as a tributary of the Úhlava River.
-
D.
Běloves
Běloves is a district or locality within the town of Náchod in the Hradec Králové Region of the Czech Republic.
-
E.
Jindřišská
Jindřišská is a central Prague street known for connecting Wenceslas Square with the historic Jindřišská Tower and serving as a major tram and traffic route in the city center.
- 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_69c008acbea48190991c6b834bb45d65 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c06253534c8190aafe70a6cf5a67ec |
completed | March 22, 2026, 9:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c243da922c819080d8d37adbb5635e |
completed | March 24, 2026, 7:57 a.m. |
Created at: March 22, 2026, 4:20 p.m.