Triple

T8933748
Position Surface form Disambiguated ID Type / Status
Subject Liberia Football Association E212721 entity
Predicate hasAbbreviation P43 FINISHED
Object LFA
LFA is the governing body responsible for overseeing and organizing football activities and competitions in Liberia.
 E767863 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: LFA | Statement: [Liberia Football Association, hasAbbreviation, LFA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: LFA
Context triple: [Liberia Football Association, hasAbbreviation, LFA]
  • A. LAF
    The Lebanese Armed Forces (LAF) are the military institution of Lebanon, responsible for defending the country’s sovereignty, maintaining internal security, and operating under a delicate sectarian balance.
  • B. LLFPA
    LLFPA is a U.S. federal law that strengthens workers’ ability to challenge pay discrimination by resetting the statute of limitations with each discriminatory paycheck.
  • C. LFLC
    LFLC is the ICAO airport code for Clermont-Ferrand Auvergne Airport in central France.
  • D. LFAC
    LFAC is the ICAO airport code for Calais–Dunkerque Airport in northern France.
  • E. LF
    LF is the commonly used abbreviation for the Linux Foundation, a nonprofit organization that supports and promotes the development of the Linux kernel and other open-source software projects.
  • 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: LFA
Triple: [Liberia Football Association, hasAbbreviation, LFA]
Generated description
LFA is the governing body responsible for overseeing and organizing football activities and competitions in Liberia.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: LFA
Target entity description: LFA is the governing body responsible for overseeing and organizing football activities and competitions in Liberia.
  • A. LAF
    The Lebanese Armed Forces (LAF) are the military institution of Lebanon, responsible for defending the country’s sovereignty, maintaining internal security, and operating under a delicate sectarian balance.
  • B. LLFPA
    LLFPA is a U.S. federal law that strengthens workers’ ability to challenge pay discrimination by resetting the statute of limitations with each discriminatory paycheck.
  • C. LFLC
    LFLC is the ICAO airport code for Clermont-Ferrand Auvergne Airport in central France.
  • D. LFAC
    LFAC is the ICAO airport code for Calais–Dunkerque Airport in northern France.
  • E. LF
    LF is the commonly used abbreviation for the Linux Foundation, a nonprofit organization that supports and promotes the development of the Linux kernel and other open-source software projects.
  • 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_69ca8395c438819087d7cb844ab5990c completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc668fa87c8190bfeda820368b89e4 completed April 1, 2026, 12:27 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfc1d965cc8190bad0a990df318698 completed April 3, 2026, 1:34 p.m.
NEDg Description generation batch_69cfc3b3044c81908631fee4ffe5c25f completed April 3, 2026, 1:42 p.m.
NED2 Entity disambiguation (via description) batch_69cfc41fca3081908d8c2515c98283de completed April 3, 2026, 1:43 p.m.
Created at: March 30, 2026, 6:57 p.m.