Triple

T2816997
Position Surface form Disambiguated ID Type / Status
Subject Barmen E54311 entity
Predicate locatedOnRiver P165 FINISHED
Object Wupper
The Wupper is a river in North Rhine-Westphalia, Germany, known for flowing through the industrial city of Wuppertal and its surrounding region.
 E364898 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: Wupper | Statement: [Barmen, locatedOnRiver, Wupper]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Wupper
Context triple: [Barmen, locatedOnRiver, Wupper]
  • A. Regnitz
    The Regnitz is a river in the German state of Bavaria that flows through cities such as Erlangen and Bamberg before joining the Main River.
  • B. Lippe
    Lippe is a historical region in northwestern Germany that once formed a small principality and later a Free State within the German Reich.
  • C. Lippe
    The Lippe is a river in western Germany that flows through North Rhine-Westphalia and is a right-bank tributary of the Rhine.
  • D. Werra
    The Werra is a major river in central Germany that forms one of the two headstreams of the Weser.
  • E. Rheine
    Rheine is a German city in the state of North Rhine-Westphalia, known for its historical town center and location along the River Ems.
  • 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: Wupper
Triple: [Barmen, locatedOnRiver, Wupper]
Generated description
The Wupper is a river in North Rhine-Westphalia, Germany, known for flowing through the industrial city of Wuppertal and its surrounding region.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Wupper
Target entity description: The Wupper is a river in North Rhine-Westphalia, Germany, known for flowing through the industrial city of Wuppertal and its surrounding region.
  • A. Regnitz
    The Regnitz is a river in the German state of Bavaria that flows through cities such as Erlangen and Bamberg before joining the Main River.
  • B. Lippe
    Lippe is a historical region in northwestern Germany that once formed a small principality and later a Free State within the German Reich.
  • C. Lippe
    The Lippe is a river in western Germany that flows through North Rhine-Westphalia and is a right-bank tributary of the Rhine.
  • D. Werra
    The Werra is a major river in central Germany that forms one of the two headstreams of the Weser.
  • E. Rheine
    Rheine is a German city in the state of North Rhine-Westphalia, known for its historical town center and location along the River Ems.
  • 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_69ab49de0af08190b3da69683be1e728 completed March 6, 2026, 9:40 p.m.
NER Named-entity recognition batch_69abde500d3c8190b435a20a0f9d3b9d completed March 7, 2026, 8:14 a.m.
NED1 Entity disambiguation (via context triple) batch_69b37e412a6c81908109b2afafe126cc completed March 13, 2026, 3:02 a.m.
NEDg Description generation batch_69b37eba29348190bfb3687afefe217b completed March 13, 2026, 3:04 a.m.
NED2 Entity disambiguation (via description) batch_69b37f1515f88190816c73aab8d2300e completed March 13, 2026, 3:05 a.m.
Created at: March 6, 2026, 9:59 p.m.