Triple
T13114116
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vorpommern-Greifswald |
E311048
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Torgelow
Torgelow is a small town in northeastern Germany’s Mecklenburg-Vorpommern region, known for its historical ironworks and surrounding forests and lakes.
|
E1023489
|
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: Torgelow | Statement: [Vorpommern-Greifswald, contains, Torgelow]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Torgelow Context triple: [Vorpommern-Greifswald, contains, Torgelow]
-
A.
Havelberg
Havelberg is a small historic town in Saxony-Anhalt, Germany, known for its medieval cathedral and location at the confluence of the Havel and Elbe rivers.
-
B.
Hardegsen
Hardegsen is a small town in Lower Saxony, Germany, known for its medieval castle and historic town center.
-
C.
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.
-
D.
Hollenstedt
Hollenstedt is a municipality in Lower Saxony, Germany, located in the district of Harburg southwest of Hamburg.
-
E.
Teterow
Teterow is a small historic town in northeastern Germany known for its medieval architecture and location in the Mecklenburg Lake District.
- 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: Torgelow Triple: [Vorpommern-Greifswald, contains, Torgelow]
Generated description
Torgelow is a small town in northeastern Germany’s Mecklenburg-Vorpommern region, known for its historical ironworks and surrounding forests and lakes.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Torgelow Target entity description: Torgelow is a small town in northeastern Germany’s Mecklenburg-Vorpommern region, known for its historical ironworks and surrounding forests and lakes.
-
A.
Havelberg
Havelberg is a small historic town in Saxony-Anhalt, Germany, known for its medieval cathedral and location at the confluence of the Havel and Elbe rivers.
-
B.
Hardegsen
Hardegsen is a small town in Lower Saxony, Germany, known for its medieval castle and historic town center.
-
C.
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.
-
D.
Hollenstedt
Hollenstedt is a municipality in Lower Saxony, Germany, located in the district of Harburg southwest of Hamburg.
-
E.
Teterow
Teterow is a small historic town in northeastern Germany known for its medieval architecture and location in the Mecklenburg Lake District.
- 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_69d806a872d08190a329806f8ff30df4 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d9817f8ee8819084078b4bec5e4f18 |
completed | April 10, 2026, 11:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6eadcd7048190aa740262679e5bab |
completed | May 3, 2026, 6:27 a.m. |
| NEDg | Description generation | batch_69f6ec25ab3081908bff1f384f6c6083 |
completed | May 3, 2026, 6:33 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f6ecc8f4e88190aac8ff2b24f2c78b |
completed | May 3, 2026, 6:35 a.m. |
Created at: April 9, 2026, 9:06 p.m.