Triple
T2097560
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ondrej Warhola |
E37016
|
entity |
| Predicate | placeOfBirth |
P1
|
FINISHED |
| Object | Miková |
E192100
|
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: Miková | Statement: [Ondrej Warhola, placeOfBirth, Miková]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Miková Context triple: [Ondrej Warhola, placeOfBirth, Miková]
-
A.
Miková
chosen
Miková is a small village in northeastern Slovakia, notable as the birthplace of Julia Warhola, mother of artist Andy Warhol.
-
B.
Kuzminki
Kuzminki is a Moscow Metro station on the Tagansko–Krasnopresnenskaya Line serving the Kuzminki District in southeastern Moscow.
-
C.
Tolkmicko
Tolkmicko is a small town in northern Poland situated on the Vistula Lagoon, known for its historic architecture and proximity to natural landscapes.
-
D.
Mirow
Mirow is a small historic town in the Mecklenburg Lake District of northeastern Germany, known for its castle island and connections to the House of Mecklenburg-Strelitz.
-
E.
Lučina
Lučina is a river in the Moravian-Silesian Region of the Czech Republic that flows through the city of Ostrava.
- 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_69a8861828948190924aa30c08806b3a |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69abba9cb84481909fe0a66c020b8864 |
completed | March 7, 2026, 5:41 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae3060b834819091dff510b89b3ec8 |
completed | March 9, 2026, 2:28 a.m. |
Created at: March 4, 2026, 7:43 p.m.