Triple

T21217910
Position Surface form Disambiguated ID Type / Status
Subject Hannes Messemer E522884 entity
Predicate givenName P17 FINISHED
Object Hannes
Hannes is a masculine given name commonly used in German-speaking countries, often as a short form of Johannes.
 E1471269 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: Hannes | Statement: [Hannes Messemer, givenName, Hannes]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Hannes
Context triple: [Hannes Messemer, givenName, Hannes]
  • A. Hans
    Hans is a masculine given name of Germanic origin commonly used in Germanic and Scandinavian countries.
  • B. Sven
    Sven is a charismatic puffin in the animated film "Happy Feet Two," admired by other characters for his apparent ability to fly and his inspirational persona.
  • C. Sven
    Sven is the lovable reindeer companion in Disney's animated film "Frozen," known for his close bond with Kristoff and his expressive, dog-like personality.
  • D. Jörg
    Jörg is a masculine given name of German origin, commonly used in German-speaking countries.
  • E. Al Hansen
    Al Hansen was an American Fluxus artist and performance pioneer known for his experimental "Happenings" and collage works that challenged traditional boundaries between art and everyday life.
  • 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: Hannes
Triple: [Hannes Messemer, givenName, Hannes]
Generated description
Hannes is a masculine given name commonly used in German-speaking countries, often as a short form of Johannes.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Hannes
Target entity description: Hannes is a masculine given name commonly used in German-speaking countries, often as a short form of Johannes.
  • A. Hans
    Hans is a masculine given name of Germanic origin commonly used in Germanic and Scandinavian countries.
  • B. Sven
    Sven is a charismatic puffin in the animated film "Happy Feet Two," admired by other characters for his apparent ability to fly and his inspirational persona.
  • C. Sven
    Sven is the lovable reindeer companion in Disney's animated film "Frozen," known for his close bond with Kristoff and his expressive, dog-like personality.
  • D. Jörg
    Jörg is a masculine given name of German origin, commonly used in German-speaking countries.
  • E. Al Hansen
    Al Hansen was an American Fluxus artist and performance pioneer known for his experimental "Happenings" and collage works that challenged traditional boundaries between art and everyday life.
  • 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_69e0b511ed84819099b449b4a111085c completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e7347613308190a1c9f4ea51591d4b completed April 21, 2026, 8:25 a.m.
NED1 Entity disambiguation (via context triple) batch_6a097edb6de4819094cf7a50670afdfa completed May 17, 2026, 8:39 a.m.
NEDg Description generation batch_6a097f5016348190aeb01856a5c57b41 completed May 17, 2026, 8:41 a.m.
NED2 Entity disambiguation (via description) batch_6a097fe399048190a1b29f16d8e46d8d completed May 17, 2026, 8:44 a.m.
Created at: April 16, 2026, 3:42 p.m.