Triple
T15127832
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jaroslav Hašek |
E361337
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Hašek |
E204402
|
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: Hašek | Statement: [Jaroslav Hašek, familyName, Hašek]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hašek Context triple: [Jaroslav Hašek, familyName, Hašek]
-
A.
Hašek
chosen
Hašek is a Czech surname most famously associated with Dominik Hašek, the legendary NHL goaltender and Hockey Hall of Famer.
-
B.
Havlíček
Havlíček is a Czech surname most famously associated with basketball Hall of Famer John Havlicek and several notable Czech cultural and public figures.
-
C.
Aleš Hemský
Aleš Hemský is a Czech former professional ice hockey right winger best known for his long NHL career with the Edmonton Oilers and his playmaking skill.
-
D.
Jaroslav Havlíček
Jaroslav Havlíček was a Czech writer best known for his psychologically oriented novels and short stories from the interwar period.
-
E.
Lumír Hanuš
Lumír Hanuš is a Czech analytical chemist and cannabis researcher best known for co-discovering the endocannabinoid anandamide.
- 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_69d85a06450081909c5a14ea9851a15e |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e005aff2648190bda885c09421758d |
completed | April 15, 2026, 9:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69feb7f865c08190ab8fd15c14d0c06c |
completed | May 9, 2026, 4:28 a.m. |
Created at: April 10, 2026, 3:06 a.m.