Triple
T14486084
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Karel Čapek |
E359231
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Čapek |
E359231
|
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: Čapek | Statement: [Karel Čapek, familyName, Čapek]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Čapek Context triple: [Karel Čapek, familyName, Čapek]
-
A.
Karel Čapek
chosen
Karel Čapek was a Czech writer and playwright best known internationally for his science fiction works, including the play "R.U.R." which introduced the word "robot" to the world.
-
B.
Patočka
Patočka is a Czech surname most notably borne by the influential 20th-century philosopher Jan Patočka.
-
C.
Havlíček
Havlíček is a Czech surname most famously associated with basketball Hall of Famer John Havlicek and several notable Czech cultural and public figures.
-
D.
Kornbluth
Kornbluth is a surname most notably associated with American science fiction writer Cyril M. Kornbluth.
-
E.
Karel
Karel is a given name, commonly used in Central and Eastern Europe, that corresponds to the English name Charles.
- 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_69d8279740308190af9df93a3af8592e |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de924ee0f08190baf68318b41fa64d |
completed | April 14, 2026, 7:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd6d8f1bf081908c37f8f41767b382 |
completed | May 8, 2026, 4:58 a.m. |
Created at: April 10, 2026, 1:20 a.m.