Triple

T21120209
Position Surface form Disambiguated ID Type / Status
Subject 2009 af2 ArenaCup E520407 entity
Predicate league P888 FINISHED
Object af2 NE NERFINISHED

How this triple was built (2 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: af2 | Statement: [2009 af2 ArenaCup, league, af2]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: af2
Context triple: [2009 af2 ArenaCup, league, af2]
  • A. af2 chosen
    af2 was a now-defunct developmental arena football league that operated as the minor league counterpart to the Arena Football League (AFL) in the United States.
  • B. AfA
    AfA is the abbreviation for the Arbeitsgemeinschaft für Arbeitnehmerfragen, a labor-oriented working group within Germany’s Social Democratic Party (SPD) that represents employees’ interests.
  • C. 2 AF
    2 AF is the commonly used abbreviation for the United States Air Force’s Second Air Force, a numbered air force responsible for conducting basic military and technical training.
  • D. AF
    AF is the two-letter ISO 3166-1 alpha-2 country code assigned to Afghanistan for international standardization and referencing.
  • E. AF
    AF is the two-letter IATA airline designator assigned to Air France, the flag carrier of France.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b50a623881909c0bbaf4f2c055e7 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e72233a43481909535560514d388be completed April 21, 2026, 7:07 a.m.
Created at: April 16, 2026, 2:55 p.m.