Triple

T11151588
Position Surface form Disambiguated ID Type / Status
Subject Hansen E263797 entity
Predicate hasNotableBearer P458 FINISHED
Object Willy Hansen
Willy Hansen was a Danish track cyclist best known for winning multiple medals, including Olympic bronze, in the early 20th century.
E909846 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: Willy Hansen | Statement: [Hansen, hasNotableBearer, Willy Hansen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Willy Hansen
Context triple: [Hansen, hasNotableBearer, Willy Hansen]
  • A. Ole Olsen
    Ole Olsen was a pioneering Danish film producer and entrepreneur who played a key role in the early development of the European film industry.
  • B. Gunnar Hansen
    Gunnar Hansen was an Icelandic-American actor best known for originating the role of Leatherface in the 1974 horror classic "The Texas Chain Saw Massacre."
  • C. Helge Petersen
    Helge Petersen was a mountaineer known for making the first recorded ascent of Greenland’s highest peak, Gunnbjørn Fjeld.
  • D. Johan Jensen
    Johan Jensen was a Danish mathematician best known for his contributions to convex analysis and for formulating the inequality that bears his name.
  • E. Terje Hansen
    Terje Hansen is an academic author known for co-authoring scholarly work with prominent economist and mathematician Herbert Scarf.
  • 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: Willy Hansen
Triple: [Hansen, hasNotableBearer, Willy Hansen]
Generated description
Willy Hansen was a Danish track cyclist best known for winning multiple medals, including Olympic bronze, in the early 20th century.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Willy Hansen
Target entity description: Willy Hansen was a Danish track cyclist best known for winning multiple medals, including Olympic bronze, in the early 20th century.
  • A. Ole Olsen
    Ole Olsen was a pioneering Danish film producer and entrepreneur who played a key role in the early development of the European film industry.
  • B. Gunnar Hansen
    Gunnar Hansen was an Icelandic-American actor best known for originating the role of Leatherface in the 1974 horror classic "The Texas Chain Saw Massacre."
  • C. Helge Petersen
    Helge Petersen was a mountaineer known for making the first recorded ascent of Greenland’s highest peak, Gunnbjørn Fjeld.
  • D. Johan Jensen
    Johan Jensen was a Danish mathematician best known for his contributions to convex analysis and for formulating the inequality that bears his name.
  • E. Terje Hansen
    Terje Hansen is an academic author known for co-authoring scholarly work with prominent economist and mathematician Herbert Scarf.
  • 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_69d6aa9ccddc8190868998c8b7beb060 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e8719e74819095413abc6c79296c completed April 9, 2026, 5:57 p.m.
NED1 Entity disambiguation (via context triple) batch_69e4835928ac81909ca2addea6fc3b5f completed April 19, 2026, 7:25 a.m.
NEDg Description generation batch_69e48715bd2081908774d325db2b6dd5 completed April 19, 2026, 7:41 a.m.
NED2 Entity disambiguation (via description) batch_69e4886c0da881909105b3a45e786ce9 completed April 19, 2026, 7:46 a.m.
Created at: April 8, 2026, 9:28 p.m.