Triple
T624296
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Harz |
E14581
|
entity |
| Predicate | hasRiverSource |
P947
|
FINISHED |
| Object |
Sieber
Sieber is a small river in the German state of Lower Saxony that flows through the Harz Mountains and into the Oder.
|
E79321
|
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: Sieber | Statement: [Harz, hasRiverSource, Sieber]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sieber Context triple: [Harz, hasRiverSource, Sieber]
-
A.
Starnberg
Starnberg is a lakeside town in Bavaria, Germany, known for its affluent residential character and scenic location on Lake Starnberg southwest of Munich.
-
B.
Mossenberg-Wöhren
Mossenberg-Wöhren is a small village in North Rhine-Westphalia, Germany, known primarily as the birthplace of former German chancellor Gerhard Schröder.
-
C.
Fürth
Fürth is a historic city in northern Bavaria, Germany, known for its well-preserved old town and proximity to Nuremberg within the Franconian metropolitan region.
-
D.
Nischel
Nischel is the local colloquial nickname for the large Karl Marx Monument in Chemnitz, Germany.
-
E.
Gerswalde
Gerswalde is a small rural municipality in the Uckermark district of Brandenburg, northeastern 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: Sieber Triple: [Harz, hasRiverSource, Sieber]
Generated description
Sieber is a small river in the German state of Lower Saxony that flows through the Harz Mountains and into the Oder.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Sieber Target entity description: Sieber is a small river in the German state of Lower Saxony that flows through the Harz Mountains and into the Oder.
-
A.
Starnberg
Starnberg is a lakeside town in Bavaria, Germany, known for its affluent residential character and scenic location on Lake Starnberg southwest of Munich.
-
B.
Mossenberg-Wöhren
Mossenberg-Wöhren is a small village in North Rhine-Westphalia, Germany, known primarily as the birthplace of former German chancellor Gerhard Schröder.
-
C.
Fürth
Fürth is a historic city in northern Bavaria, Germany, known for its well-preserved old town and proximity to Nuremberg within the Franconian metropolitan region.
-
D.
Nischel
Nischel is the local colloquial nickname for the large Karl Marx Monument in Chemnitz, Germany.
-
E.
Gerswalde
Gerswalde is a small rural municipality in the Uckermark district of Brandenburg, northeastern 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_69a4934b17c881909ace8270e8ddd202 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a514b514819088e7b6b7e4675905 |
completed | March 1, 2026, 8:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a56c4b64088190a033462dd923f5b2 |
completed | March 2, 2026, 10:54 a.m. |
| NEDg | Description generation | batch_69a56d4af33081908c3c5649003e86e4 |
completed | March 2, 2026, 10:58 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69a56dd4bb808190a5562a5f8bcf2910 |
completed | March 2, 2026, 11 a.m. |
Created at: March 1, 2026, 7:35 p.m.