Triple
T1502406
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Havlicek |
E33824
|
entity |
| Predicate | hasVariantSpelling |
P457
|
FINISHED |
| Object |
Havlíček
Havlíček is a Czech surname most famously associated with basketball Hall of Famer John Havlicek and several notable Czech cultural and public figures.
|
E171352
|
NE FINISHED |
How this triple was built (4 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: Havlíček | Statement: [Havlicek, hasVariantSpelling, Havlíček]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Havlíček Context triple: [Havlicek, hasVariantSpelling, Havlíček]
-
A.
Vojtech
Vojtech is a masculine given name of Slavic origin, commonly used in Central and Eastern Europe.
-
B.
Karel Gut
Karel Gut was a prominent Czech ice hockey coach and former player who significantly influenced Czechoslovak and later Czech ice hockey at the international level.
-
C.
Havel
The Havel is a river in northeastern Germany that flows through Berlin and Brandenburg before joining the Elbe.
-
D.
Karel
Karel is a given name, commonly used in Central and Eastern Europe, that corresponds to the English name Charles.
-
E.
František Kučera
František Kučera is a former Czech ice hockey defenceman known for his international success with the Czech national team and a lengthy professional career in Europe and the NHL.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Havlíček Triple: [Havlicek, hasVariantSpelling, Havlíček]
Generated description
Havlíček is a Czech surname most famously associated with basketball Hall of Famer John Havlicek and several notable Czech cultural and public figures.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Havlíček Target entity description: Havlíček is a Czech surname most famously associated with basketball Hall of Famer John Havlicek and several notable Czech cultural and public figures.
-
A.
Vojtech
Vojtech is a masculine given name of Slavic origin, commonly used in Central and Eastern Europe.
-
B.
Karel Gut
Karel Gut was a prominent Czech ice hockey coach and former player who significantly influenced Czechoslovak and later Czech ice hockey at the international level.
-
C.
Havel
The Havel is a river in northeastern Germany that flows through Berlin and Brandenburg before joining the Elbe.
-
D.
Karel
Karel is a given name, commonly used in Central and Eastern Europe, that corresponds to the English name Charles.
-
E.
František Kučera
František Kučera is a former Czech ice hockey defenceman known for his international success with the Czech national team and a lengthy professional career in Europe and the NHL.
- F. None of above. chosen
Provenance (5 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_69a885f352a4819099b24ff15489dede |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a8872fae4c81908e7d6961e6c5fa96 |
completed | March 4, 2026, 7:25 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad1cb578e4819082d254462e10e4f0 |
completed | March 8, 2026, 6:52 a.m. |
| NEDg | Description generation | batch_69ad1d34656481909949b4bfd83c6142 |
completed | March 8, 2026, 6:54 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ad1dd7b34c8190b6957be2112506dd |
completed | March 8, 2026, 6:57 a.m. |
Created at: March 4, 2026, 7:24 p.m.