Triple

T3119637
Position Surface form Disambiguated ID Type / Status
Subject Wales national football team E65150 entity
Predicate fifaCode P6278 FINISHED
Object WAL
WAL is the official FIFA country code used to represent the Wales national football team in international competitions and records.
 E330091 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: WAL | Statement: [Wales national football team, fifaCode, WAL]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: WAL
Context triple: [Wales national football team, fifaCode, WAL]
  • A. WAW
    WAW is the three-letter IATA airport code for Warsaw Chopin Airport, the primary international airport serving Warsaw, Poland.
  • B. WAS
    WAS is the standard three-letter abbreviation used for the Washington Commanders NFL franchise.
  • C. WAS
    WAS is the station code for Washington, D.C.’s main intercity and commuter rail hub, Union Station.
  • D. WAS
    WAS is the standard three-letter abbreviation used for the NBA team Washington Wizards.
  • E. WLM
    WLM (Workload Manager) is an IBM z/OS component that dynamically manages and prioritizes system workloads to meet performance goals and service-level objectives.
  • 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: WAL
Triple: [Wales national football team, fifaCode, WAL]
Generated description
WAL is the official FIFA country code used to represent the Wales national football team in international competitions and records.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: WAL
Target entity description: WAL is the official FIFA country code used to represent the Wales national football team in international competitions and records.
  • A. WAW
    WAW is the three-letter IATA airport code for Warsaw Chopin Airport, the primary international airport serving Warsaw, Poland.
  • B. WAS
    WAS is the standard three-letter abbreviation used for the Washington Commanders NFL franchise.
  • C. WAS
    WAS is the station code for Washington, D.C.’s main intercity and commuter rail hub, Union Station.
  • D. WAS
    WAS is the standard three-letter abbreviation used for the NBA team Washington Wizards.
  • E. WLM
    WLM (Workload Manager) is an IBM z/OS component that dynamically manages and prioritizes system workloads to meet performance goals and service-level objectives.
  • 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_69ad857fcc088190b0c4d45a5cde6f61 completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ada4eb6a6081909df41f67999eb4ff completed March 8, 2026, 4:33 p.m.
NED1 Entity disambiguation (via context triple) batch_69b20f67b80c8190849581cf1829d840 completed March 12, 2026, 12:57 a.m.
NEDg Description generation batch_69b2135f05c88190b926556828a038ac completed March 12, 2026, 1:14 a.m.
NED2 Entity disambiguation (via description) batch_69b214268d588190996d909297baaffc completed March 12, 2026, 1:17 a.m.
Created at: March 8, 2026, 3:04 p.m.