Triple
T432249
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mecklenburg-Vorpommern |
E9737
|
entity |
| Predicate | hasMajorCity |
P316
|
FINISHED |
| Object |
Greifswald
Greifswald is a historic Hanseatic university city in northeastern Germany, located near the Baltic Sea.
|
E159331
|
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: Greifswald | Statement: [Mecklenburg-Vorpommern, hasMajorCity, Greifswald]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Greifswald Context triple: [Mecklenburg-Vorpommern, hasMajorCity, Greifswald]
-
A.
Rostock
Rostock is a historic Hanseatic city in northern Germany known for its significant seaport on the Baltic Sea and its long maritime and trading tradition.
-
B.
Schwerin
Schwerin is a historic city in northern Germany known for its picturesque lakeside setting and landmark Schwerin Castle.
-
C.
Wismar
Wismar is a historic Hanseatic port city on Germany’s Baltic Sea coast, known for its well-preserved medieval architecture and UNESCO-listed old town.
-
D.
Lübeck
Lübeck is a historic Hanseatic city in northern Germany renowned for its medieval architecture and long-standing role as a key trading hub on the Baltic Sea.
-
E.
Göttingen
Göttingen is a historic university city in Lower Saxony, Germany, renowned for its prestigious Georg-August University and contributions to science and mathematics.
- 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: Greifswald Triple: [Mecklenburg-Vorpommern, hasMajorCity, Greifswald]
Generated description
Greifswald is a historic Hanseatic university city in northeastern Germany, located near the Baltic Sea.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Greifswald Target entity description: Greifswald is a historic Hanseatic university city in northeastern Germany, located near the Baltic Sea.
-
A.
Rostock
Rostock is a historic Hanseatic city in northern Germany known for its significant seaport on the Baltic Sea and its long maritime and trading tradition.
-
B.
Schwerin
Schwerin is a historic city in northern Germany known for its picturesque lakeside setting and landmark Schwerin Castle.
-
C.
Wismar
Wismar is a historic Hanseatic port city on Germany’s Baltic Sea coast, known for its well-preserved medieval architecture and UNESCO-listed old town.
-
D.
Lübeck
Lübeck is a historic Hanseatic city in northern Germany renowned for its medieval architecture and long-standing role as a key trading hub on the Baltic Sea.
-
E.
Göttingen
Göttingen is a historic university city in Lower Saxony, Germany, renowned for its prestigious Georg-August University and contributions to science and mathematics.
- 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_69a2e801e1d48190b505d1dd336b52ac |
completed | Feb. 28, 2026, 1:05 p.m. |
| NER | Named-entity recognition | batch_69a2eef07e748190b05392778f3de980 |
completed | Feb. 28, 2026, 1:34 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69acddeda4f8819080d37aea0fd4b092 |
completed | March 8, 2026, 2:24 a.m. |
| NEDg | Description generation | batch_69acde6b92bc819081bc5c1aae64d981 |
completed | March 8, 2026, 2:26 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69acded2e6a48190af7f135a0a4d8588 |
completed | March 8, 2026, 2:28 a.m. |
Created at: Feb. 28, 2026, 1:11 p.m.