Triple
T9582957
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tomasz |
E231217
|
entity |
| Predicate | equivalentTo |
P6530
|
FINISHED |
| Object | Tomáš |
E588700
|
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: [Tomasz, equivalentTo, Tomáš]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tomáš Context triple: [Tomasz, equivalentTo, Tomáš]
-
A.
Tomáš
chosen
Tomáš is a masculine given name commonly used in Czech and Slovak cultures, equivalent to Thomas in English.
-
B.
Timotej
Timotej is a masculine given name, common in Slavic countries, that is equivalent to Timothy.
-
C.
Zdeněk
Zdeněk is a Czech given name commonly used for males, equivalent to the English name Sidney or Dennis in some contexts.
-
D.
Vojtech
Vojtech is a masculine given name of Slavic origin, commonly used in Central and Eastern Europe.
-
E.
Bohuslav
Bohuslav is a Czech masculine given name of Slavic origin, historically borne by several notable figures including composers and politicians.
- 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_69ca848161688190a68d514a0a9d5129 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd99cebaf081908033536a53fbf668 |
completed | April 1, 2026, 10:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d16176ccf081908eb079ddd762ba28 |
completed | April 4, 2026, 7:07 p.m. |
Created at: March 30, 2026, 8:05 p.m.