Triple
T13016538
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ján Svatopluk Presl |
E322565
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object |
Květena česká
Květena česká is a foundational 19th-century botanical work that systematically documents the flora of the Czech lands.
|
E1016686
|
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: Květena česká | Statement: [Ján Svatopluk Presl, notableWork, Květena česká]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Květena česká Context triple: [Ján Svatopluk Presl, notableWork, Květena česká]
-
A.
Bechyně
Bechyně is a historic spa town in the Czech Republic known for its ceramics tradition and picturesque location above the Lužnice River.
-
B.
Libuše
Libuše is a Czech opera by Bedřich Smetana, centered on the legendary princess Libuše who prophesies the glory of Prague and the Czech nation.
-
C.
Zelníčková
Zelníčková is a Czech surname, notably borne by Ivana Marie Zelníčková, the Czech-American businesswoman and former wife of Donald Trump.
-
D.
Viktorka
Viktorka is the popular nickname of FC Viktoria Plzeň, a professional football club from Plzeň in the Czech Republic.
-
E.
Loučka
Loučka is a river in the Czech Republic that serves as a left-bank tributary of the Svratka River.
- 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: Květena česká Triple: [Ján Svatopluk Presl, notableWork, Květena česká]
Generated description
Květena česká is a foundational 19th-century botanical work that systematically documents the flora of the Czech lands.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Květena česká Target entity description: Květena česká is a foundational 19th-century botanical work that systematically documents the flora of the Czech lands.
-
A.
Bechyně
Bechyně is a historic spa town in the Czech Republic known for its ceramics tradition and picturesque location above the Lužnice River.
-
B.
Libuše
Libuše is a Czech opera by Bedřich Smetana, centered on the legendary princess Libuše who prophesies the glory of Prague and the Czech nation.
-
C.
Zelníčková
Zelníčková is a Czech surname, notably borne by Ivana Marie Zelníčková, the Czech-American businesswoman and former wife of Donald Trump.
-
D.
Viktorka
Viktorka is the popular nickname of FC Viktoria Plzeň, a professional football club from Plzeň in the Czech Republic.
-
E.
Loučka
Loučka is a river in the Czech Republic that serves as a left-bank tributary of the Svratka River.
- 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_69d807657e8c8190bd9435ee2f823845 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d97ecd04748190ade2530ee5db35fe |
completed | April 10, 2026, 10:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6c1147974819090007c21383d5c86 |
completed | May 3, 2026, 3:29 a.m. |
| NEDg | Description generation | batch_69f6c562d10c8190b76dbf50a0101bae |
completed | May 3, 2026, 3:47 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f6c635fc888190891a79da9d7984a0 |
completed | May 3, 2026, 3:51 a.m. |
Created at: April 9, 2026, 8:51 p.m.