Triple
T22254792
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marián Hossa |
E550069
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Marián |
—
|
NE NERFINISHED |
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: Marián | Statement: [Marián Hossa, givenName, Marián]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Marián Context triple: [Marián Hossa, givenName, Marián]
-
A.
Marián
chosen
Marián is a masculine given name commonly used in Slovak and other Central European cultures.
-
B.
Matej
Matej is a masculine given name commonly used in Slavic countries, equivalent to Matthew in English.
-
C.
Ján
Ján is a common Slovak male given name, equivalent to "John" in English.
-
D.
Mária
Mária is the Hungarian and Slovak form of the given name Mary, commonly used in Central and Eastern Europe.
-
E.
Matúš
Matúš is the Slovak form of the given name Matthew, commonly used in Slovakia and other Slovak-speaking communities.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e11e42adb8819087714772ea606709 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f138c1d70881908df47b0f818c0022 |
completed | April 28, 2026, 10:46 p.m. |
Created at: April 16, 2026, 8:39 p.m.