Triple

T1336177
Position Surface form Disambiguated ID Type / Status
Subject Missouri–Kansas–Texas Railroad E28754 entity
Predicate shortName P43 FINISHED
Object MKT
MKT was the reporting mark and common abbreviation for the Missouri–Kansas–Texas Railroad, a major regional railroad that served the south-central United States.
 E154788 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: MKT | Statement: [Missouri–Kansas–Texas Railroad, shortName, MKT]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: MKT
Context triple: [Missouri–Kansas–Texas Railroad, shortName, MKT]
  • A. MAR
    MAR is the three-letter ISO 3166-1 alpha-3 country code assigned to Morocco.
  • B. MK
    MK is the two-letter ISO 3166-1 alpha-2 country code assigned to North Macedonia.
  • C. Marken
    Marken is a small, picturesque former island village in the Netherlands known for its traditional wooden houses, fishing heritage, and distinctive cultural character.
  • D. KMK
    KMK is the central coordinating body of Germany’s state education and cultural ministers, responsible for harmonizing policies across the federal states.
  • E. .mt
    .mt is the country code top-level domain (ccTLD) assigned to Malta for use on the internet.
  • 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: MKT
Triple: [Missouri–Kansas–Texas Railroad, shortName, MKT]
Generated description
MKT was the reporting mark and common abbreviation for the Missouri–Kansas–Texas Railroad, a major regional railroad that served the south-central United States.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: MKT
Target entity description: MKT was the reporting mark and common abbreviation for the Missouri–Kansas–Texas Railroad, a major regional railroad that served the south-central United States.
  • A. MAR
    MAR is the three-letter ISO 3166-1 alpha-3 country code assigned to Morocco.
  • B. MK
    MK is the two-letter ISO 3166-1 alpha-2 country code assigned to North Macedonia.
  • C. Marken
    Marken is a small, picturesque former island village in the Netherlands known for its traditional wooden houses, fishing heritage, and distinctive cultural character.
  • D. KMK
    KMK is the central coordinating body of Germany’s state education and cultural ministers, responsible for harmonizing policies across the federal states.
  • E. .mt
    .mt is the country code top-level domain (ccTLD) assigned to Malta for use on the internet.
  • 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_69a498561a508190a3e1bc137c2b866a completed March 1, 2026, 7:49 p.m.
NER Named-entity recognition batch_69a4c1ecb5208190a9eadda113c91e66 completed March 1, 2026, 10:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69acc62b9bd081909dbe22cbea03f21f completed March 8, 2026, 12:43 a.m.
NEDg Description generation batch_69acc6c204a88190a3171898e6e1bb91 completed March 8, 2026, 12:45 a.m.
NED2 Entity disambiguation (via description) batch_69acc7d8df108190bf92ca5e33987d04 completed March 8, 2026, 12:50 a.m.
Created at: March 1, 2026, 7:55 p.m.