Triple

T921353
Position Surface form Disambiguated ID Type / Status
Subject zur Lippe-Biesterfeld E19890 entity
Predicate region P40 FINISHED
Object Lippe
Lippe is a historical region in northwestern Germany that once formed a small principality and later a Free State within the German Reich.
E138916 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: Lippe | Statement: [zur Lippe-Biesterfeld, region, Lippe]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lippe
Context triple: [zur Lippe-Biesterfeld, region, Lippe]
  • A. Leine
    The Leine is a major river in central Germany that flows through the federal state of Lower Saxony, passing cities such as Göttingen and Hanover before joining the Aller.
  • B. Weser
    The Weser is a major river in northwestern Germany that flows through several federal states before emptying into the North Sea.
  • C. 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.
  • D. Werra
    The Werra is a major river in central Germany that forms one of the two headstreams of the Weser.
  • E. Ruhr
    The Ruhr is a river in western Germany that flows through the Ruhr industrial region before joining the Rhine.
  • 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: Lippe
Triple: [zur Lippe-Biesterfeld, region, Lippe]
Generated description
Lippe is a historical region in northwestern Germany that once formed a small principality and later a Free State within the German Reich.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Lippe
Target entity description: Lippe is a historical region in northwestern Germany that once formed a small principality and later a Free State within the German Reich.
  • A. Leine
    The Leine is a major river in central Germany that flows through the federal state of Lower Saxony, passing cities such as Göttingen and Hanover before joining the Aller.
  • B. Weser
    The Weser is a major river in northwestern Germany that flows through several federal states before emptying into the North Sea.
  • C. 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.
  • D. Werra
    The Werra is a major river in central Germany that forms one of the two headstreams of the Weser.
  • E. Ruhr
    The Ruhr is a river in western Germany that flows through the Ruhr industrial region before joining the Rhine.
  • 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_69a493a099788190a696d9d8408cbaf4 completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4b313cb908190ad78b3a54e4f2eb7 completed March 1, 2026, 9:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac82f25c088190ae32593e6edbb8d0 completed March 7, 2026, 7:56 p.m.
NEDg Description generation batch_69ac83c99fe481909b62ba635c4bc98c completed March 7, 2026, 8 p.m.
NED2 Entity disambiguation (via description) batch_69ac843a0bdc819099ee4ae275ef5669 completed March 7, 2026, 8:02 p.m.
Created at: March 1, 2026, 7:40 p.m.