Triple

T13312421
Position Surface form Disambiguated ID Type / Status
Subject Witten E317101 entity
Predicate hasRiver P165 FINISHED
Object Elbsche
Elbsche is a small river in North Rhine-Westphalia, Germany, that flows through the city of Witten and its surrounding region.
 E1033251 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: Elbsche | Statement: [Witten, hasRiver, Elbsche]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Elbsche
Context triple: [Witten, hasRiver, Elbsche]
  • A. Eckersbach
    Eckersbach is a district of the city of Zwickau in the German state of Saxony, known primarily as a residential area.
  • B. Eschwege
    Eschwege is a small historic town in the German state of Hesse, known for its medieval architecture and location near the Werra River.
  • C. Hohenelbe
    Hohenelbe is the German name for the Czech town of Vrchlabí, a gateway to the Krkonoše (Giant) Mountains region.
  • D. Teltow
    Teltow is a town in the German state of Brandenburg, located just southwest of Berlin and known for its historical core and proximity to the capital.
  • E. Elbbach
    Elbbach is a river in western Germany that flows through the town of Hadamar and is a tributary of the Lahn River.
  • 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: Elbsche
Triple: [Witten, hasRiver, Elbsche]
Generated description
Elbsche is a small river in North Rhine-Westphalia, Germany, that flows through the city of Witten and its surrounding region.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Elbsche
Target entity description: Elbsche is a small river in North Rhine-Westphalia, Germany, that flows through the city of Witten and its surrounding region.
  • A. Eckersbach
    Eckersbach is a district of the city of Zwickau in the German state of Saxony, known primarily as a residential area.
  • B. Eschwege
    Eschwege is a small historic town in the German state of Hesse, known for its medieval architecture and location near the Werra River.
  • C. Hohenelbe
    Hohenelbe is the German name for the Czech town of Vrchlabí, a gateway to the Krkonoše (Giant) Mountains region.
  • D. Teltow
    Teltow is a town in the German state of Brandenburg, located just southwest of Berlin and known for its historical core and proximity to the capital.
  • E. Elbbach
    Elbbach is a river in western Germany that flows through the town of Hadamar and is a tributary of the Lahn River.
  • 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_69d806b40ab4819094adf6c374f4811a completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d990f6d34c8190ba19dc2df7d42c22 completed April 11, 2026, 12:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69f716e7b9a48190a33b04df8ad45ed8 completed May 3, 2026, 9:35 a.m.
NEDg Description generation batch_69f717b868608190971c38f26b61cf28 completed May 3, 2026, 9:39 a.m.
NED2 Entity disambiguation (via description) batch_69f7186b6218819096c67e9dd9af609f completed May 3, 2026, 9:42 a.m.
Created at: April 9, 2026, 9:29 p.m.