Triple

T15045666
Position Surface form Disambiguated ID Type / Status
Subject Gorgon City E379217 entity
Predicate collaboratedWith P435 FINISHED
Object MK
MK is an American DJ, record producer, and remixer best known for his influential house music tracks and club remixes since the 1990s.
E1133856 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: MK | Statement: [Gorgon City, collaboratedWith, MK]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: MK
Context triple: [Gorgon City, collaboratedWith, MK]
  • A. MK
    MK is the two-letter ISO 3166-1 alpha-2 country code assigned to North Macedonia.
  • B. MK
    MK is the commonly used abbreviation for Umkhonto we Sizwe, the former armed wing of South Africa’s African National Congress during the anti-apartheid struggle.
  • C. MK
    MK is the postal area code designation for Milton Keynes and its surrounding region in the United Kingdom.
  • D. MK
    MK is the two-letter IATA airline designator assigned to Air Mauritius, the flag carrier airline of Mauritius.
  • E. M-K
    M-K is the commonly used abbreviation for Morrison-Knudsen, a major American engineering and construction company known for large-scale infrastructure projects.
  • 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: MK
Triple: [Gorgon City, collaboratedWith, MK]
Generated description
MK is an American DJ, record producer, and remixer best known for his influential house music tracks and club remixes since the 1990s.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: MK
Target entity description: MK is an American DJ, record producer, and remixer best known for his influential house music tracks and club remixes since the 1990s.
  • A. MK
    MK is the two-letter ISO 3166-1 alpha-2 country code assigned to North Macedonia.
  • B. MK
    MK is the commonly used abbreviation for Umkhonto we Sizwe, the former armed wing of South Africa’s African National Congress during the anti-apartheid struggle.
  • C. MK
    MK is the postal area code designation for Milton Keynes and its surrounding region in the United Kingdom.
  • D. MK
    MK is the two-letter IATA airline designator assigned to Air Mauritius, the flag carrier airline of Mauritius.
  • E. M-K
    M-K is the commonly used abbreviation for Morrison-Knudsen, a major American engineering and construction company known for large-scale infrastructure projects.
  • 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_69d85cd64d108190853797a95c11cc45 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69ded830c3c08190a87b81abbbb75377 completed April 15, 2026, 12:13 a.m.
NED1 Entity disambiguation (via context triple) batch_69fe9de54380819084568664b63322d2 completed May 9, 2026, 2:37 a.m.
NEDg Description generation batch_69fea0791f1c81908dcad401fa3ac245 completed May 9, 2026, 2:48 a.m.
NED2 Entity disambiguation (via description) batch_69fea11a35a88190a5ad6f261fd2d9dc completed May 9, 2026, 2:51 a.m.
Created at: April 10, 2026, 3 a.m.