Triple

T13812926
Position Surface form Disambiguated ID Type / Status
Subject Hans-Peter Wild E331938 entity
Predicate hasGivenName P17 FINISHED
Object Hans-Peter
Hans-Peter is a masculine German given name commonly used in German-speaking countries, often as a compound of the names Hans and Peter.
E1063118 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: Hans-Peter | Statement: [Hans-Peter Wild, hasGivenName, Hans-Peter]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hans-Peter
Context triple: [Hans-Peter Wild, hasGivenName, Hans-Peter]
  • A. Hans-Jürgen
    Hans-Jürgen is a masculine German given name, typically used as a compound first name combining "Hans" and "Jürgen."
  • B. Hans-Dieter
    Hans-Dieter is the full given first name of German football coach Hansi Flick.
  • C. Hans Peters
    Hans Peters was a film art director known for his work on classic mid-20th-century Hollywood productions.
  • D. Jens Hennersdorf
    Jens Hennersdorf is a German local politician who serves as the mayor of the municipality of Burkhardtsdorf in Saxony.
  • E. Hans Weiss
    Hans Weiss is a relatively common German personal name shared by multiple individuals, including figures in fields such as literature, journalism, and the arts.
  • 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: Hans-Peter
Triple: [Hans-Peter Wild, hasGivenName, Hans-Peter]
Generated description
Hans-Peter is a masculine German given name commonly used in German-speaking countries, often as a compound of the names Hans and Peter.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Hans-Peter
Target entity description: Hans-Peter is a masculine German given name commonly used in German-speaking countries, often as a compound of the names Hans and Peter.
  • A. Hans-Jürgen
    Hans-Jürgen is a masculine German given name, typically used as a compound first name combining "Hans" and "Jürgen."
  • B. Hans-Dieter
    Hans-Dieter is the full given first name of German football coach Hansi Flick.
  • C. Hans Peters
    Hans Peters was a film art director known for his work on classic mid-20th-century Hollywood productions.
  • D. Jens Hennersdorf
    Jens Hennersdorf is a German local politician who serves as the mayor of the municipality of Burkhardtsdorf in Saxony.
  • E. Hans Weiss
    Hans Weiss is a relatively common German personal name shared by multiple individuals, including figures in fields such as literature, journalism, and the arts.
  • 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_69d81c59f8808190a851bc56afdc55e9 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de027198f8819095da3e714ac241f5 completed April 14, 2026, 9:01 a.m.
NED1 Entity disambiguation (via context triple) batch_69f7b8de34a4819090c99cb78b941003 completed May 3, 2026, 9:06 p.m.
NEDg Description generation batch_69f7b974fce88190ace5030555b7b5f1 completed May 3, 2026, 9:09 p.m.
NED2 Entity disambiguation (via description) batch_69f7ba936c4481908757699ff22d3904 completed May 3, 2026, 9:13 p.m.
Created at: April 9, 2026, 10:12 p.m.