Triple
T9123408
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | LIP |
E218913
|
entity |
| Predicate | usedInTown |
P87209
|
FINISHED |
| Object |
Dörentrup
Dörentrup is a small municipality in the Lippe district of North Rhine-Westphalia, Germany, known for its rural character and location within the Teutoburg Forest region.
|
E786766
|
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: Dörentrup | Statement: [LIP, usedInTown, Dörentrup]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dörentrup Context triple: [LIP, usedInTown, Dörentrup]
-
A.
Donsbach
Donsbach is a village and district of the town of Dillenburg in the Lahn-Dill-Kreis region of Hesse, Germany.
-
B.
Dierdorf
Dierdorf is a surname most prominently associated with former American football player and sportscaster Dan Dierdorf.
-
C.
Adendorf
Adendorf is a village-sized district within the municipality of Wachtberg in the Rhein-Sieg-Kreis region of North Rhine-Westphalia, Germany.
-
D.
Burgstädt
Burgstädt is a small town in the German state of Saxony, known for its traditional architecture and location near the city of Chemnitz.
-
E.
Suhrendorf
Suhrendorf is a small coastal village on the German Baltic Sea island of Ummanz, known for its rural charm and proximity to nature and water sports areas.
- 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: Dörentrup Triple: [LIP, usedInTown, Dörentrup]
Generated description
Dörentrup is a small municipality in the Lippe district of North Rhine-Westphalia, Germany, known for its rural character and location within the Teutoburg Forest region.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Dörentrup Target entity description: Dörentrup is a small municipality in the Lippe district of North Rhine-Westphalia, Germany, known for its rural character and location within the Teutoburg Forest region.
-
A.
Donsbach
Donsbach is a village and district of the town of Dillenburg in the Lahn-Dill-Kreis region of Hesse, Germany.
-
B.
Dierdorf
Dierdorf is a surname most prominently associated with former American football player and sportscaster Dan Dierdorf.
-
C.
Adendorf
Adendorf is a village-sized district within the municipality of Wachtberg in the Rhein-Sieg-Kreis region of North Rhine-Westphalia, Germany.
-
D.
Burgstädt
Burgstädt is a small town in the German state of Saxony, known for its traditional architecture and location near the city of Chemnitz.
-
E.
Suhrendorf
Suhrendorf is a small coastal village on the German Baltic Sea island of Ummanz, known for its rural charm and proximity to nature and water sports areas.
- 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_69ca83dddd548190983b96c664f7f367 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cca8b5fa188190be6465e74cf26915 |
completed | April 1, 2026, 5:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d07758ce3c819088e78674a7da5a06 |
completed | April 4, 2026, 2:28 a.m. |
| NEDg | Description generation | batch_69d0782d305481909a2b41615e890863 |
completed | April 4, 2026, 2:32 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d0789ef4288190bf4d52e7ed47bd9b |
completed | April 4, 2026, 2:34 a.m. |
Created at: March 30, 2026, 7:17 p.m.