Triple
T3226117
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thomas |
E67625
|
entity |
| Predicate | cognateWith |
P2525
|
FINISHED |
| Object | Tomáš (Czech) |
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 (Czech) | Statement: [Thomas, cognateWith, Tomáš (Czech)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tomáš (Czech) Context triple: [Thomas, cognateWith, Tomáš (Czech)]
-
A.
Timotej
Timotej is a masculine given name, common in Slavic countries, that is equivalent to Timothy.
-
B.
Tomas
chosen
Tomas is a masculine given name commonly used in various European and Latin American countries, often equivalent to "Thomas" in English.
-
C.
Vojtech
Vojtech is a masculine given name of Slavic origin, commonly used in Central and Eastern Europe.
-
D.
Roman Čechmánek
Roman Čechmánek was a Czech professional ice hockey goaltender who starred in international play for the Czech national team and later played in the NHL, most notably for the Philadelphia Flyers.
-
E.
Tomasz
Tomasz is a masculine given name of Aramaic origin, widely used in Poland and other European countries, equivalent to the English name Thomas.
- 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_69ad858c61888190a31196310d9b30b5 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69adaeb4cd3481908af8a2c9b6c0742d |
completed | March 8, 2026, 5:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b2625eaa708190b23ca6e575d664a2 |
completed | March 12, 2026, 6:51 a.m. |
Created at: March 8, 2026, 3:08 p.m.