Triple

T18792559
Position Surface form Disambiguated ID Type / Status
Subject Kentucky Distillers’ Association E459552 entity
Predicate hasAbbreviation P43 FINISHED
Object KDA
KDA is a trade organization representing Kentucky’s distilled spirits industry, including bourbon and other whiskey producers.
 E1343382 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: KDA | Statement: [Kentucky Distillers’ Association, hasAbbreviation, KDA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: KDA
Context triple: [Kentucky Distillers’ Association, hasAbbreviation, KDA]
  • A. KDA
    KDA is a British electronic music production project best known for its club-ready house tracks and high-profile collaborations with pop and dance artists.
  • B. KAD
    KAD is the IATA airport code for Kaduna International Airport in Kaduna, Nigeria.
  • C. Ka
    Ka is the introspective poet and protagonist of Orhan Pamuk’s novel "Snow," whose return to Turkey and entanglement in political and personal conflicts drive the story’s exploration of faith, identity, and modernity.
  • D. Ka
    Ka is an American underground rapper and producer from Brownsville, Brooklyn, known for his minimalist, introspective style and dense, poetic lyricism.
  • E. Ka
    Ka was an early ancient Egyptian king of the First Dynasty period, known from tomb inscriptions at Abydos and considered one of the first rulers to use a royal serekh.
  • 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: KDA
Triple: [Kentucky Distillers’ Association, hasAbbreviation, KDA]
Generated description
KDA is a trade organization representing Kentucky’s distilled spirits industry, including bourbon and other whiskey producers.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: KDA
Target entity description: KDA is a trade organization representing Kentucky’s distilled spirits industry, including bourbon and other whiskey producers.
  • A. KDA
    KDA is a British electronic music production project best known for its club-ready house tracks and high-profile collaborations with pop and dance artists.
  • B. KAD
    KAD is the IATA airport code for Kaduna International Airport in Kaduna, Nigeria.
  • C. Ka
    Ka is an American underground rapper and producer from Brownsville, Brooklyn, known for his minimalist, introspective style and dense, poetic lyricism.
  • D. Ka
    Ka was an early ancient Egyptian king of the First Dynasty period, known from tomb inscriptions at Abydos and considered one of the first rulers to use a royal serekh.
  • E. Ka
    Ka is the introspective poet and protagonist of Orhan Pamuk’s novel "Snow," whose return to Turkey and entanglement in political and personal conflicts drive the story’s exploration of faith, identity, and modernity.
  • 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_69d8d396f54c8190ba49db31e8743842 completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e59787e5988190883ed575ab4b6dec completed April 20, 2026, 3:03 a.m.
NED1 Entity disambiguation (via context triple) batch_6a05471e942c81908de4ec52f4c0bb6f completed May 14, 2026, 3:53 a.m.
NEDg Description generation batch_6a0548414b188190bf64dc5a0673b9cd completed May 14, 2026, 3:57 a.m.
NED2 Entity disambiguation (via description) batch_6a0548d472bc81909d874e0b27ca3736 completed May 14, 2026, 4 a.m.
Created at: April 10, 2026, 11:53 a.m.