Triple
T14927004
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dresden–Děčín railway |
E372158
|
entity |
| Predicate | hasBorderStation |
P14206
|
FINISHED |
| Object |
Schöna
Schöna is a small German railway station on the Elbe River near the Czech border, serving as a key cross-border stop between Germany and the Czech Republic.
|
E1127270
|
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: Schöna | Statement: [Dresden–Děčín railway, hasBorderStation, Schöna]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Schöna Context triple: [Dresden–Děčín railway, hasBorderStation, Schöna]
-
A.
Bad Schönau
Bad Schönau is a small spa town in Lower Austria known for its therapeutic mineral springs and tranquil rural setting.
-
B.
Schöngarth
Schöngarth is a German surname most notably associated with Eberhard Schöngarth, a high-ranking Nazi SS officer and war criminal during World War II.
-
C.
Schöpfl
Schöpfl is a prominent mountain in Lower Austria known as the highest peak of the Vienna Woods range.
-
D.
Schönwölkau
Schönwölkau is a small municipality in the state of Saxony in eastern Germany, situated within the wider Leipzig metropolitan area.
-
E.
Schönau im Schwarzwald
Schönau im Schwarzwald is a small town in Germany’s Black Forest region, known for its scenic mountainous surroundings and traditional Black Forest character.
- 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: Schöna Triple: [Dresden–Děčín railway, hasBorderStation, Schöna]
Generated description
Schöna is a small German railway station on the Elbe River near the Czech border, serving as a key cross-border stop between Germany and the Czech Republic.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Schöna Target entity description: Schöna is a small German railway station on the Elbe River near the Czech border, serving as a key cross-border stop between Germany and the Czech Republic.
-
A.
Bad Schönau
Bad Schönau is a small spa town in Lower Austria known for its therapeutic mineral springs and tranquil rural setting.
-
B.
Schöngarth
Schöngarth is a German surname most notably associated with Eberhard Schöngarth, a high-ranking Nazi SS officer and war criminal during World War II.
-
C.
Schöpfl
Schöpfl is a prominent mountain in Lower Austria known as the highest peak of the Vienna Woods range.
-
D.
Schönwölkau
Schönwölkau is a small municipality in the state of Saxony in eastern Germany, situated within the wider Leipzig metropolitan area.
-
E.
Schönau im Schwarzwald
Schönau im Schwarzwald is a small town in Germany’s Black Forest region, known for its scenic mountainous surroundings and traditional Black Forest character.
- 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_69d85cc9da0c81908d583ca3f63a3908 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded633da0c8190b39f606212e48e71 |
completed | April 15, 2026, 12:05 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe72c4f9c481909642efccb29f71d4 |
completed | May 8, 2026, 11:33 p.m. |
| NEDg | Description generation | batch_69fe744b9c048190ae2a64da53d8ffac |
completed | May 8, 2026, 11:39 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69fe74d510808190a2379a2380fc327e |
completed | May 8, 2026, 11:42 p.m. |
Created at: April 10, 2026, 2:35 a.m.