Triple

T555726
Position Surface form Disambiguated ID Type / Status
Subject Kevin Durant E11936 entity
Predicate hasNickname P39 FINISHED
Object KD
KD is the widely used nickname of Kevin Durant, an elite NBA scorer and multi-time champion regarded as one of the greatest basketball players of his generation.
 E69778 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: KD | Statement: [Kevin Durant, hasNickname, KD]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: KD
Context triple: [Kevin Durant, hasNickname, KD]
  • A. DK
    DK is the ISO 3166-1 alpha-2 country code for Denmark, a Nordic nation in Northern Europe.
  • B. KC
    KC is a common shorthand nickname for Kansas City, Missouri, a major Midwestern U.S. city known for its jazz heritage, barbecue, and sports teams.
  • C. KP
    KP is the commonly used abbreviation for Khyber Pakhtunkhwa, a province in northwestern Pakistan known for its mountainous terrain and diverse ethnic communities.
  • D. EK
    EK is the commonly used abbreviation for the First Chamber of the Austrian Parliament (Erste Kammer).
  • E. KG
    KG is the post-nominal abbreviation used by Knights of the Order of the Garter, the highest order of chivalry in the United Kingdom.
  • 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: KD
Triple: [Kevin Durant, hasNickname, KD]
Generated description
KD is the widely used nickname of Kevin Durant, an elite NBA scorer and multi-time champion regarded as one of the greatest basketball players of his generation.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: KD
Target entity description: KD is the widely used nickname of Kevin Durant, an elite NBA scorer and multi-time champion regarded as one of the greatest basketball players of his generation.
  • A. DK
    DK is the ISO 3166-1 alpha-2 country code for Denmark, a Nordic nation in Northern Europe.
  • B. KC
    KC is a common shorthand nickname for Kansas City, Missouri, a major Midwestern U.S. city known for its jazz heritage, barbecue, and sports teams.
  • C. KP
    KP is the commonly used abbreviation for Khyber Pakhtunkhwa, a province in northwestern Pakistan known for its mountainous terrain and diverse ethnic communities.
  • D. EK
    EK is the commonly used abbreviation for the First Chamber of the Austrian Parliament (Erste Kammer).
  • E. KG
    KG is the widely used nickname of Kevin Garnett, a Hall of Fame NBA forward known for his intensity, defensive prowess, and versatility.
  • 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_69a4932941d08190815efd422f0b4ca7 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a4991dd7008190a6c1bc8bc832456d completed March 1, 2026, 7:53 p.m.
NED1 Entity disambiguation (via context triple) batch_69a4e644f41c819099743a6c4f2815e4 completed March 2, 2026, 1:22 a.m.
NEDg Description generation batch_69a4e6cfdbf48190814dfb9d2bd8dbf5 completed March 2, 2026, 1:24 a.m.
NED2 Entity disambiguation (via description) batch_69a4e79f2a8881909210998edba8a2a8 completed March 2, 2026, 1:27 a.m.
Created at: March 1, 2026, 7:32 p.m.