Triple
T10728838
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nordwestmecklenburg |
E253019
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Boltenhagen
Boltenhagen is a Baltic Sea seaside resort town in northern Germany known for its beaches and tourism.
|
E964811
|
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: Boltenhagen | Statement: [Nordwestmecklenburg, contains, Boltenhagen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Boltenhagen Context triple: [Nordwestmecklenburg, contains, Boltenhagen]
-
A.
Treuenbrietzen
Treuenbrietzen is a historic town in the German state of Brandenburg, known for its medieval architecture and role in Reformation-era history.
-
B.
Ziegenhain
Ziegenhain is a historic town in the German state of Hesse, known for its medieval fortifications and role in regional conflicts.
-
C.
Geiersthal
Geiersthal is a small municipality in the Bavarian Forest region of southeastern Germany.
-
D.
Böhlen
Böhlen is a small town in the Leipzig district of Saxony, Germany, known for its lignite mining and power generation industries.
-
E.
Briesen
Briesen is a small town in present-day Germany best known as the birthplace of Nobel Prize–winning chemist Walther Nernst.
- 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: Boltenhagen Triple: [Nordwestmecklenburg, contains, Boltenhagen]
Generated description
Boltenhagen is a Baltic Sea seaside resort town in northern Germany known for its beaches and tourism.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Boltenhagen Target entity description: Boltenhagen is a Baltic Sea seaside resort town in northern Germany known for its beaches and tourism.
-
A.
Treuenbrietzen
Treuenbrietzen is a historic town in the German state of Brandenburg, known for its medieval architecture and role in Reformation-era history.
-
B.
Ziegenhain
Ziegenhain is a historic town in the German state of Hesse, known for its medieval fortifications and role in regional conflicts.
-
C.
Geiersthal
Geiersthal is a small municipality in the Bavarian Forest region of southeastern Germany.
-
D.
Böhlen
Böhlen is a small town in the Leipzig district of Saxony, Germany, known for its lignite mining and power generation industries.
-
E.
Briesen
Briesen is a small town in present-day Germany best known as the birthplace of Nobel Prize–winning chemist Walther Nernst.
- 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_69d6aa5d8be481909a43218b2bfdbe95 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d70fc92a18819089cc67afee1c9b96 |
completed | April 9, 2026, 2:32 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f5f62d41448190ab65fb9c81d4d673 |
completed | May 2, 2026, 1:03 p.m. |
| NEDg | Description generation | batch_69f600b51f488190a85a8f10f190b3c0 |
completed | May 2, 2026, 1:48 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f601e7f3b0819098a2245b9f9316b9 |
completed | May 2, 2026, 1:53 p.m. |
Created at: April 8, 2026, 9:14 p.m.