Triple

T1622560
Position Surface form Disambiguated ID Type / Status
Subject Yokohama F. Marinos E35063 entity
Predicate shortName P43 FINISHED
Object YFM
YFM is the abbreviated name commonly used for Yokohama F. Marinos, a professional football club based in Yokohama, Japan.
 E184477 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: YFM | Statement: [Yokohama F. Marinos, shortName, YFM]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: YFM
Context triple: [Yokohama F. Marinos, shortName, YFM]
  • A. YKF
    YKF is the IATA airport code for Region of Waterloo International Airport serving the Kitchener–Waterloo area in Ontario, Canada.
  • B. YHM
    YHM is the IATA airport code for John C. Munro Hamilton International Airport, a regional passenger and cargo airport serving the Hamilton, Ontario area in Canada.
  • C. FMF
    FMF is the commonly used abbreviation for the Mexican Football Federation, the governing body of professional and amateur soccer in Mexico.
  • D. YEM
    YEM is the three-letter ISO 3166-1 alpha-3 country code assigned to Yemen for international identification and data standards.
  • E. YV
    YV is the IATA airline designator used to identify Mesa Airlines in flight schedules and ticketing systems.
  • 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: YFM
Triple: [Yokohama F. Marinos, shortName, YFM]
Generated description
YFM is the abbreviated name commonly used for Yokohama F. Marinos, a professional football club based in Yokohama, Japan.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: YFM
Target entity description: YFM is the abbreviated name commonly used for Yokohama F. Marinos, a professional football club based in Yokohama, Japan.
  • A. YKF
    YKF is the IATA airport code for Region of Waterloo International Airport serving the Kitchener–Waterloo area in Ontario, Canada.
  • B. YHM
    YHM is the IATA airport code for John C. Munro Hamilton International Airport, a regional passenger and cargo airport serving the Hamilton, Ontario area in Canada.
  • C. FMF
    FMF is the commonly used abbreviation for the Mexican Football Federation, the governing body of professional and amateur soccer in Mexico.
  • D. YEM
    YEM is the three-letter ISO 3166-1 alpha-3 country code assigned to Yemen for international identification and data standards.
  • E. YV
    YV is the IATA airline designator used to identify Mesa Airlines in flight schedules and ticketing systems.
  • 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_69a886023194819080a3fccd6e325d0e completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a909cf3c7481909ddbe6a6596bb0c8 completed March 5, 2026, 4:42 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad58c9ed4c8190a546ec4977f60695 completed March 8, 2026, 11:08 a.m.
NEDg Description generation batch_69ad5a0a88ac819096598917c2c9de48 completed March 8, 2026, 11:14 a.m.
NED2 Entity disambiguation (via description) batch_69ad5a85071c8190bab5cefcd918bb8d completed March 8, 2026, 11:16 a.m.
Created at: March 4, 2026, 7:28 p.m.