Triple
T7646020
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Örtze |
E173122
|
entity |
| Predicate | flowsThrough |
P225
|
FINISHED |
| Object |
Faßberg
Faßberg is a municipality in Lower Saxony, Germany, known for its location in the Lüneburg Heath and its historical military airbase.
|
E690128
|
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: Faßberg | Statement: [Örtze, flowsThrough, Faßberg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Faßberg Context triple: [Örtze, flowsThrough, Faßberg]
-
A.
Gevelsberg
Gevelsberg is a town in North Rhine-Westphalia, Germany, situated in the Ennepe-Ruhr district within the Ruhr metropolitan region.
-
B.
Trakehnen
Trakehnen was a renowned East Prussian stud farm and village, historically famous as the cradle of the Trakehner horse breed.
-
C.
Borgholzhausen
Borgholzhausen is a small town in North Rhine-Westphalia, Germany, known for its location on the Teutoburg Forest and its historical ties to the former County of Ravensberg.
-
D.
Ennigerloh
Ennigerloh is a small town in the German state of North Rhine-Westphalia, known as the birthplace of mathematician Karl Weierstrass.
-
E.
Treuenbrietzen
Treuenbrietzen is a historic town in the German state of Brandenburg, known for its medieval architecture and role in Reformation-era history.
- 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: Faßberg Triple: [Örtze, flowsThrough, Faßberg]
Generated description
Faßberg is a municipality in Lower Saxony, Germany, known for its location in the Lüneburg Heath and its historical military airbase.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Faßberg Target entity description: Faßberg is a municipality in Lower Saxony, Germany, known for its location in the Lüneburg Heath and its historical military airbase.
-
A.
Gevelsberg
Gevelsberg is a town in North Rhine-Westphalia, Germany, situated in the Ennepe-Ruhr district within the Ruhr metropolitan region.
-
B.
Trakehnen
Trakehnen was a renowned East Prussian stud farm and village, historically famous as the cradle of the Trakehner horse breed.
-
C.
Borgholzhausen
Borgholzhausen is a small town in North Rhine-Westphalia, Germany, known for its location on the Teutoburg Forest and its historical ties to the former County of Ravensberg.
-
D.
Ennigerloh
Ennigerloh is a small town in the German state of North Rhine-Westphalia, known as the birthplace of mathematician Karl Weierstrass.
-
E.
Treuenbrietzen
Treuenbrietzen is a historic town in the German state of Brandenburg, known for its medieval architecture and role in Reformation-era history.
- 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_69c6995360188190968ee57b72a1627f |
completed | March 27, 2026, 2:50 p.m. |
| NER | Named-entity recognition | batch_69c6faf3bd388190a8cb0f13322a7c00 |
completed | March 27, 2026, 9:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c91f49faec8190b4920097d52896f3 |
completed | March 29, 2026, 12:47 p.m. |
| NEDg | Description generation | batch_69c91fc5a1048190b5d4c988efa99713 |
completed | March 29, 2026, 12:49 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c92043ee988190a1ce0ee6090eb5fc |
completed | March 29, 2026, 12:51 p.m. |
Created at: March 27, 2026, 3:58 p.m.