Triple
T15539131
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aš |
E370428
|
entity |
| Predicate | hasAdministrativePart |
P3892
|
FINISHED |
| Object |
Dolní Paseky
Dolní Paseky is a small settlement that forms one of the administrative parts of the town of Aš in the Karlovy Vary Region of the Czech Republic.
|
E1163697
|
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: Dolní Paseky | Statement: [Aš, hasAdministrativePart, Dolní Paseky]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dolní Paseky Context triple: [Aš, hasAdministrativePart, Dolní Paseky]
-
A.
Osek
Osek is a town in the Czech Republic historically associated with the family origins of writer Franz Kafka’s father, Hermann Kafka.
-
B.
Prachatice
Prachatice is a historic town in the Czech Republic known for its well-preserved medieval center and former importance as a stop on the Golden Salt Trade Route.
-
C.
Bubeneč
Bubeneč is a residential and diplomatic district in Prague known for its embassies, green spaces, and proximity to Stromovka park.
-
D.
Střešovice
Střešovice is a residential district in Prague known for its historic villas, quiet streets, and proximity to Prague Castle.
-
E.
Nymburk
Nymburk is a historic town in the Czech Republic known for its medieval fortifications and location on the Elbe 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: Dolní Paseky Triple: [Aš, hasAdministrativePart, Dolní Paseky]
Generated description
Dolní Paseky is a small settlement that forms one of the administrative parts of the town of Aš in the Karlovy Vary Region of the Czech Republic.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Dolní Paseky Target entity description: Dolní Paseky is a small settlement that forms one of the administrative parts of the town of Aš in the Karlovy Vary Region of the Czech Republic.
-
A.
Osek
Osek is a town in the Czech Republic historically associated with the family origins of writer Franz Kafka’s father, Hermann Kafka.
-
B.
Prachatice
Prachatice is a historic town in the Czech Republic known for its well-preserved medieval center and former importance as a stop on the Golden Salt Trade Route.
-
C.
Bubeneč
Bubeneč is a residential and diplomatic district in Prague known for its embassies, green spaces, and proximity to Stromovka park.
-
D.
Střešovice
Střešovice is a residential district in Prague known for its historic villas, quiet streets, and proximity to Prague Castle.
-
E.
Nymburk
Nymburk is a historic town in the Czech Republic known for its medieval fortifications and location on the Elbe 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_69d85cc521a08190921fb50319dddc34 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04430b5188190a555a3cd4fb0c61c |
completed | April 16, 2026, 2:06 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff4556ad008190a411ccd3ef0d1e89 |
completed | May 9, 2026, 2:31 p.m. |
| NEDg | Description generation | batch_69ff47590f5c81908da35e6d85452eee |
completed | May 9, 2026, 2:40 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ff47d81e408190888b86f3f69ca76e |
completed | May 9, 2026, 2:42 p.m. |
Created at: April 10, 2026, 4:07 a.m.