Triple
T9495211
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wagria |
E228986
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Grömitz
Grömitz is a Baltic Sea resort town in northern Germany known for its long sandy beaches and seaside tourism.
|
E806278
|
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: Grömitz | Statement: [Wagria, contains, Grömitz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Grömitz Context triple: [Wagria, contains, Grömitz]
-
A.
Geringswalde
Geringswalde is a small town in the Free State of Saxony in eastern Germany, known for its rural character and location within the Central Saxon region.
-
B.
Dömitz
Dömitz is a small historic town in northern Germany, known for its well-preserved fortress and location on the Elbe River near the former inner-German border.
-
C.
Schwedt
Schwedt is a town in northeastern Germany, located on the Oder River near the Polish border, known for its industrial facilities and cross-border regional ties.
-
D.
Wietzendorf
Wietzendorf is a small municipality in Lower Saxony, Germany, known for its rural character and location in the Lüneburg Heath region.
-
E.
Zinnowitz
Zinnowitz is a seaside resort town on Germany’s Baltic Sea coast, known for its sandy beaches, historic spa architecture, and tourism on the island of Usedom.
- 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: Grömitz Triple: [Wagria, contains, Grömitz]
Generated description
Grömitz is a Baltic Sea resort town in northern Germany known for its long sandy beaches and seaside tourism.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Grömitz Target entity description: Grömitz is a Baltic Sea resort town in northern Germany known for its long sandy beaches and seaside tourism.
-
A.
Geringswalde
Geringswalde is a small town in the Free State of Saxony in eastern Germany, known for its rural character and location within the Central Saxon region.
-
B.
Dömitz
Dömitz is a small historic town in northern Germany, known for its well-preserved fortress and location on the Elbe River near the former inner-German border.
-
C.
Schwedt
Schwedt is a town in northeastern Germany, located on the Oder River near the Polish border, known for its industrial facilities and cross-border regional ties.
-
D.
Wietzendorf
Wietzendorf is a small municipality in Lower Saxony, Germany, known for its rural character and location in the Lüneburg Heath region.
-
E.
Zinnowitz
Zinnowitz is a seaside resort town on Germany’s Baltic Sea coast, known for its sandy beaches, historic spa architecture, and tourism on the island of Usedom.
- 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_69ca84753660819098e8d416e89e26ae |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd95eb87b081908fc7255598cd9a24 |
completed | April 1, 2026, 10:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1526994dc81908fe637f806ebf390 |
completed | April 4, 2026, 6:03 p.m. |
| NEDg | Description generation | batch_69d1538ad2308190aaa529b402e09eca |
completed | April 4, 2026, 6:08 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d153e07ac48190bb39edc64e03b57d |
completed | April 4, 2026, 6:09 p.m. |
Created at: March 30, 2026, 7:56 p.m.