Triple
T81406
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oskar Morgenstern |
E1635
|
entity |
| Predicate | birthPlace |
P1
|
FINISHED |
| Object |
Görlitz
Görlitz is a historic city in eastern Germany on the Lusatian Neisse River, known for its well-preserved old town and role as a popular film location.
|
E32852
|
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: Görlitz | Statement: [Oskar Morgenstern, birthPlace, Görlitz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Görlitz Context triple: [Oskar Morgenstern, birthPlace, Görlitz]
-
A.
Chemnitz
Chemnitz is a city in eastern Germany known for its industrial heritage and post-reunification urban redevelopment.
-
B.
Cieszyn Silesia
Cieszyn Silesia is a historical and ethnically diverse borderland region centered around the city of Cieszyn, spanning areas of present-day Poland and the Czech Republic.
-
C.
Glogów
Glogów is a historic town in western Poland on the Oder River, known for its medieval origins and reconstructed Old Town.
-
D.
Plzeň
Plzeň is a major city in western Bohemia in the Czech Republic, known for its brewing tradition and industrial heritage.
-
E.
Szczecin
Szczecin is a large Polish city and important maritime and industrial center in northwestern Poland, situated near the Baltic Sea and the German border.
- 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: Görlitz Triple: [Oskar Morgenstern, birthPlace, Görlitz]
Generated description
Görlitz is a historic city in eastern Germany on the Lusatian Neisse River, known for its well-preserved old town and role as a popular film location.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Görlitz Target entity description: Görlitz is a historic city in eastern Germany on the Lusatian Neisse River, known for its well-preserved old town and role as a popular film location.
-
A.
Chemnitz
Chemnitz is a city in eastern Germany known for its industrial heritage and post-reunification urban redevelopment.
-
B.
Cieszyn Silesia
Cieszyn Silesia is a historical and ethnically diverse borderland region centered around the city of Cieszyn, spanning areas of present-day Poland and the Czech Republic.
-
C.
Glogów
Glogów is a historic town in western Poland on the Oder River, known for its medieval origins and reconstructed Old Town.
-
D.
Plzeň
Plzeň is a major city in western Bohemia in the Czech Republic, known for its brewing tradition and industrial heritage.
-
E.
Szczecin
Szczecin is a large Polish city and important maritime and industrial center in northwestern Poland, situated near the Baltic Sea and the German border.
- 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_69a24c60d19c8190a1b6c105ca59ef5b |
completed | Feb. 28, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69a24f354d088190972791051d2d99f8 |
completed | Feb. 28, 2026, 2:13 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a376555f5081909f8a6593aa5858c4 |
completed | Feb. 28, 2026, 11:12 p.m. |
| NEDg | Description generation | batch_69a376c686048190aec0abd9c6999663 |
completed | Feb. 28, 2026, 11:14 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69a377aa34cc81908820a5c970d1ecf6 |
completed | Feb. 28, 2026, 11:18 p.m. |
Created at: Feb. 28, 2026, 2:06 a.m.