Triple

T7021230
Position Surface form Disambiguated ID Type / Status
Subject Morrison-Knudsen E162828 entity
Predicate alternateName P39 FINISHED
Object 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.
 E638016 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: M-K | Statement: [Morrison-Knudsen, alternateName, M-K]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: M-K
Context triple: [Morrison-Knudsen, alternateName, M-K]
  • A. MK
    MK is the postal area code designation for Milton Keynes and its surrounding region in the United Kingdom.
  • 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 two-letter IATA airline designator assigned to Air Mauritius, the flag carrier airline of Mauritius.
  • D. MK
    MK is the two-letter ISO 3166-1 alpha-2 country code assigned to North Macedonia.
  • E. KMK
    KMK is the central coordinating body of Germany’s state education and cultural ministers, responsible for harmonizing policies across the federal states.
  • 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: M-K
Triple: [Morrison-Knudsen, alternateName, M-K]
Generated description
M-K is the commonly used abbreviation for Morrison-Knudsen, a major American engineering and construction company known for large-scale infrastructure projects.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: M-K
Target entity description: M-K is the commonly used abbreviation for Morrison-Knudsen, a major American engineering and construction company known for large-scale infrastructure projects.
  • A. 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.
  • B. MK
    MK is the postal area code designation for Milton Keynes and its surrounding region in the United Kingdom.
  • C. MK
    MK is the two-letter IATA airline designator assigned to Air Mauritius, the flag carrier airline of Mauritius.
  • D. MK
    MK is the two-letter ISO 3166-1 alpha-2 country code assigned to North Macedonia.
  • E. KMK
    KMK is the central coordinating body of Germany’s state education and cultural ministers, responsible for harmonizing policies across the federal states.
  • 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_69c6885b26248190a857541e3d10e299 completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6e1ec34a48190b64cafb94e2f8706 completed March 27, 2026, 8 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7885104e881909be62c2eb12e0bcf completed March 28, 2026, 7:50 a.m.
NEDg Description generation batch_69c7891785288190974db0bca4b8f265 completed March 28, 2026, 7:53 a.m.
NED2 Entity disambiguation (via description) batch_69c78982bc308190aeffc3f786a82327 completed March 28, 2026, 7:55 a.m.
Created at: March 27, 2026, 2:35 p.m.