Triple
T16089682
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nádraží Holešovice |
E390327
|
entity |
| Predicate | hasAdjacentStation |
P231
|
FINISHED |
| Object |
Kobylisy
Kobylisy is a residential district in northern Prague, Czech Republic, known for its metro station on Line C and its postwar housing estates.
|
E1234747
|
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: Kobylisy | Statement: [Nádraží Holešovice, hasAdjacentStation, Kobylisy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kobylisy Context triple: [Nádraží Holešovice, hasAdjacentStation, Kobylisy]
-
A.
Krasnobród
Krasnobród is a small town in southeastern Poland known for its historical role in World War II and as a local tourist and spa destination in the Roztocze region.
-
B.
Brzesko
Brzesko is a town in southern Poland known for its historical architecture and regional brewing traditions.
-
C.
Cieszyn
Cieszyn is a historic town in southern Poland on the Olza River, known for its shared Polish-Czech heritage and well-preserved old town.
-
D.
Kraśnik
Kraśnik is a town in eastern Poland known for its historical architecture and location within the Lublin region.
-
E.
Hrubieszów
Hrubieszów is a historic town in eastern Poland near the Ukrainian border, known for its multicultural heritage and location in the Lublin region.
- 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: Kobylisy Triple: [Nádraží Holešovice, hasAdjacentStation, Kobylisy]
Generated description
Kobylisy is a residential district in northern Prague, Czech Republic, known for its metro station on Line C and its postwar housing estates.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kobylisy Target entity description: Kobylisy is a residential district in northern Prague, Czech Republic, known for its metro station on Line C and its postwar housing estates.
-
A.
Krasnobród
Krasnobród is a small town in southeastern Poland known for its historical role in World War II and as a local tourist and spa destination in the Roztocze region.
-
B.
Brzesko
Brzesko is a town in southern Poland known for its historical architecture and regional brewing traditions.
-
C.
Cieszyn
Cieszyn is a historic town in southern Poland on the Olza River, known for its shared Polish-Czech heritage and well-preserved old town.
-
D.
Kraśnik
Kraśnik is a town in eastern Poland known for its historical architecture and location within the Lublin region.
-
E.
Hrubieszów
Hrubieszów is a historic town in eastern Poland near the Ukrainian border, known for its multicultural heritage and location in the Lublin region.
- 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_69d87f198bc48190a8b7e53ca15b7ead |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e1845161908190adca2af94710b2cc |
completed | April 17, 2026, 12:52 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00b274fa3481908b019036cd2ae627 |
completed | May 10, 2026, 4:29 p.m. |
| NEDg | Description generation | batch_6a00b3ba6b048190a25e17c41921c370 |
completed | May 10, 2026, 4:35 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a00b43279688190bf012544b9e6ec41 |
completed | May 10, 2026, 4:37 p.m. |
Created at: April 10, 2026, 4:59 a.m.