Triple
T22088409
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alena Mihulová |
E545846
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object |
Sestřičky
Sestřičky is a Czech film best known for featuring actress Alena Mihulová in a prominent role.
|
E1518544
|
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: Sestřičky | Statement: [Alena Mihulová, notableWork, Sestřičky]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sestřičky Context triple: [Alena Mihulová, notableWork, Sestřičky]
-
A.
Stodůlky
Stodůlky is a district in the western part of Prague, Czech Republic, known for its large residential estates and modern commercial developments.
-
B.
Chrudimka
Chrudimka is a river in the Czech Republic that flows through the Pardubice Region and is a tributary of the Elbe.
-
C.
Hrádeček
Hrádeček is a small rural settlement in the Czech Republic best known as the longtime country residence and retreat of playwright and former president Václav Havel, where he also died.
-
D.
Třemešné
Třemešné is a small municipality and village in the Plzeň Region of the Czech Republic.
-
E.
Studénka
Studénka is a town in the Moravian-Silesian Region of the Czech Republic, known historically for its railway engineering and carriage works.
- 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: Sestřičky Triple: [Alena Mihulová, notableWork, Sestřičky]
Generated description
Sestřičky is a Czech film best known for featuring actress Alena Mihulová in a prominent role.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Sestřičky Target entity description: Sestřičky is a Czech film best known for featuring actress Alena Mihulová in a prominent role.
-
A.
Stodůlky
Stodůlky is a district in the western part of Prague, Czech Republic, known for its large residential estates and modern commercial developments.
-
B.
Chrudimka
Chrudimka is a river in the Czech Republic that flows through the Pardubice Region and is a tributary of the Elbe.
-
C.
Hrádeček
Hrádeček is a small rural settlement in the Czech Republic best known as the longtime country residence and retreat of playwright and former president Václav Havel, where he also died.
-
D.
Třemešné
Třemešné is a small municipality and village in the Plzeň Region of the Czech Republic.
-
E.
Studénka
Studénka is a town in the Moravian-Silesian Region of the Czech Republic, known historically for its railway engineering and carriage works.
- 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_69e11e36d03c8190a83a1ba802b7231b |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f128e3a98481908a7b3dc3f2a90276 |
completed | April 28, 2026, 9:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0a87982c6c8190af25c334ba1437d6 |
completed | May 18, 2026, 3:29 a.m. |
| NEDg | Description generation | batch_6a0a89500af08190a4837a0ef6d7042d |
completed | May 18, 2026, 3:36 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0a8a353b3881908230b1dc890c896f |
completed | May 18, 2026, 3:40 a.m. |
Created at: April 16, 2026, 8:29 p.m.