Triple

T5926189
Position Surface form Disambiguated ID Type / Status
Subject Oakton–Skokie station E131815 entity
Predicate hasStationCode P1289 FINISHED
Object OK
OK is the station code assigned to Oakton–Skokie station on the Chicago Transit Authority’s Yellow Line.
 E557318 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: OK | Statement: [Oakton–Skokie station, hasStationCode, OK]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: OK
Context triple: [Oakton–Skokie station, hasStationCode, OK]
  • A. OK
    OK is the official two-letter United States Postal Service abbreviation for the state of Oklahoma.
  • B. OK
    "OK" is a song by British singer-songwriter James Blunt, known for its emotive lyrics and melodic pop style.
  • C. OKKK
    OKKK is the former ICAO airport code that was once used to identify Kuwait International Airport in international aviation.
  • D. EOK
    EOK is the Estonian Olympic Committee, the national body responsible for organizing Estonia’s participation in the Olympic Games and promoting Olympic sports in the country.
  • E. KO
    KO is the New York Stock Exchange ticker symbol for The Coca-Cola Company, one of the world’s largest and most recognizable beverage corporations.
  • 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: OK
Triple: [Oakton–Skokie station, hasStationCode, OK]
Generated description
OK is the station code assigned to Oakton–Skokie station on the Chicago Transit Authority’s Yellow Line.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: OK
Target entity description: OK is the station code assigned to Oakton–Skokie station on the Chicago Transit Authority’s Yellow Line.
  • A. OK
    OK is the official two-letter United States Postal Service abbreviation for the state of Oklahoma.
  • B. OK
    "OK" is a song by British singer-songwriter James Blunt, known for its emotive lyrics and melodic pop style.
  • C. OKKK
    OKKK is the former ICAO airport code that was once used to identify Kuwait International Airport in international aviation.
  • D. EOK
    EOK is the Estonian Olympic Committee, the national body responsible for organizing Estonia’s participation in the Olympic Games and promoting Olympic sports in the country.
  • E. KO
    KO is the New York Stock Exchange ticker symbol for The Coca-Cola Company, one of the world’s largest and most recognizable beverage corporations.
  • 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_69c0085b75e88190a632f9691f9da48b completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c038542e548190b335df9a948c8490 completed March 22, 2026, 6:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0c04e5af8819095f15cfbc1f13c46 completed March 23, 2026, 4:23 a.m.
NEDg Description generation batch_69c0c23cc6d081909ce27bfb6a6f33d4 completed March 23, 2026, 4:31 a.m.
NED2 Entity disambiguation (via description) batch_69c0c2deec7c81909d9949cb28f0211f completed March 23, 2026, 4:34 a.m.
Created at: March 22, 2026, 4 p.m.