Triple
T23095815
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ribnitz-Damgarten |
E575883
|
entity |
| Predicate | formedByMergerOf |
P77
|
FINISHED |
| Object |
Damgarten
Damgarten is a former town in northeastern Germany that later became part of the merged town of Ribnitz-Damgarten in Mecklenburg-Vorpommern.
|
E1570536
|
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: Damgarten | Statement: [Ribnitz-Damgarten, formedByMergerOf, Damgarten]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Damgarten Context triple: [Ribnitz-Damgarten, formedByMergerOf, Damgarten]
-
A.
Enchenberg
Enchenberg is a small commune in northeastern France, situated in the Moselle department within the historical region of Lorraine.
-
B.
Rottenegg
Rottenegg is a small village that forms one of the local subdivisions of the Bavarian town of Geisenfeld in Germany.
-
C.
Siedenburg
Siedenburg is a small municipality in Lower Saxony, Germany, situated within the rural Diepholz district.
-
D.
Haselbach
Haselbach is a small municipality in the Straubing-Bogen district of Lower Bavaria in southeastern Germany.
-
E.
Todenfeld
Todenfeld is a village and district of the town of Rheinbach in the Rhein-Sieg-Kreis region of North Rhine-Westphalia, Germany.
- 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: Damgarten Triple: [Ribnitz-Damgarten, formedByMergerOf, Damgarten]
Generated description
Damgarten is a former town in northeastern Germany that later became part of the merged town of Ribnitz-Damgarten in Mecklenburg-Vorpommern.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Damgarten Target entity description: Damgarten is a former town in northeastern Germany that later became part of the merged town of Ribnitz-Damgarten in Mecklenburg-Vorpommern.
-
A.
Enchenberg
Enchenberg is a small commune in northeastern France, situated in the Moselle department within the historical region of Lorraine.
-
B.
Rottenegg
Rottenegg is a small village that forms one of the local subdivisions of the Bavarian town of Geisenfeld in Germany.
-
C.
Siedenburg
Siedenburg is a small municipality in Lower Saxony, Germany, situated within the rural Diepholz district.
-
D.
Haselbach
Haselbach is a small municipality in the Straubing-Bogen district of Lower Bavaria in southeastern Germany.
-
E.
Todenfeld
Todenfeld is a village and district of the town of Rheinbach in the Rhein-Sieg-Kreis region of North Rhine-Westphalia, Germany.
- 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_69e245c060b48190a9bd61a47a16db17 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f18de522e48190a37e6c2fda2de465 |
completed | April 29, 2026, 4:49 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0c15bb9ed48190987f072de415cf7d |
completed | May 19, 2026, 7:48 a.m. |
| NEDg | Description generation | batch_6a0c19727a24819094a8a5257b1ce69e |
completed | May 19, 2026, 8:04 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0c1a0a6974819083858e111c093e11 |
completed | May 19, 2026, 8:06 a.m. |
Created at: April 17, 2026, 3:57 p.m.