Triple
T6908813
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wittmund district |
E159879
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Friedeburg
Friedeburg is a small municipality in Lower Saxony, Germany, known for its rural character and location within the East Frisian region.
|
E633483
|
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: Friedeburg | Statement: [Wittmund district, contains, Friedeburg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Friedeburg Context triple: [Wittmund district, contains, Friedeburg]
-
A.
Biebrich
Biebrich is a district of Wiesbaden in the German state of Hesse, historically known as an independent town on the Rhine and the site of the Baroque Biebrich Palace.
-
B.
Schwarmstedt
Schwarmstedt is a municipality in Lower Saxony, Germany, situated in the Heidekreis district along the River Aller.
-
C.
Wallhausen
Wallhausen is a village in present-day Saxony-Anhalt, Germany, historically notable as the birthplace of Otto I, Holy Roman Emperor.
-
D.
Hagen
Hagen is a surname of German origin borne by various notable individuals across fields such as music, sports, and academia.
-
E.
Hagen
Hagen is a city in the Ruhr region of North Rhine-Westphalia in western Germany, known historically as an industrial and transport hub.
- 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: Friedeburg Triple: [Wittmund district, contains, Friedeburg]
Generated description
Friedeburg is a small municipality in Lower Saxony, Germany, known for its rural character and location within the East Frisian region.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Friedeburg Target entity description: Friedeburg is a small municipality in Lower Saxony, Germany, known for its rural character and location within the East Frisian region.
-
A.
Biebrich
Biebrich is a district of Wiesbaden in the German state of Hesse, historically known as an independent town on the Rhine and the site of the Baroque Biebrich Palace.
-
B.
Schwarmstedt
Schwarmstedt is a municipality in Lower Saxony, Germany, situated in the Heidekreis district along the River Aller.
-
C.
Wallhausen
Wallhausen is a village in present-day Saxony-Anhalt, Germany, historically notable as the birthplace of Otto I, Holy Roman Emperor.
-
D.
Hagen
Hagen is a city in the Ruhr region of North Rhine-Westphalia in western Germany, known historically as an industrial and transport hub.
-
E.
Hagen
Hagen is a surname of German origin borne by various notable individuals across fields such as music, sports, and academia.
- 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_69c68839ccb88190b4aa5cc1aca3448f |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6d9be98748190b5cb698e66e3aa42 |
completed | March 27, 2026, 7:25 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c761800804819082320a03f035f05b |
completed | March 28, 2026, 5:05 a.m. |
| NEDg | Description generation | batch_69c7629031608190b1ef76e969c97925 |
completed | March 28, 2026, 5:09 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c76329a47081909b47894ba0e1cad1 |
completed | March 28, 2026, 5:12 a.m. |
Created at: March 27, 2026, 2:25 p.m.