Triple
T4424400
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tomáš Nosek |
E95175
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Tomáš |
E143480
|
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: Tomáš | Statement: [Tomáš Nosek, givenName, Tomáš]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tomáš Context triple: [Tomáš Nosek, givenName, Tomáš]
-
A.
Timotej
Timotej is a masculine given name, common in Slavic countries, that is equivalent to Timothy.
-
B.
Vojtech
Vojtech is a masculine given name of Slavic origin, commonly used in Central and Eastern Europe.
-
C.
Jozef
Jozef is a masculine given name of Hebrew origin, commonly used in Central and Eastern Europe as a variant of Joseph.
-
D.
Oldřich
Oldřich is a Czech masculine given name traditionally borne by several notable historical and cultural figures in the Czech lands.
-
E.
Tomas
chosen
Tomas is a masculine given name commonly used in various European and Latin American countries, often equivalent to "Thomas" in English.
- 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_69b3453a36908190b95a79a297ca083c |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b3554ca5208190ba2661616dcf071c |
completed | March 13, 2026, 12:07 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5f62f7eb88190a02669845126e790 |
completed | March 14, 2026, 11:58 p.m. |
Created at: March 12, 2026, 11:30 p.m.