Triple

T11058801
Position Surface form Disambiguated ID Type / Status
Subject MPLA E261450 entity
Predicate armedWing P4347 FINISHED
Object FAPLA
FAPLA was the military wing of Angola’s ruling MPLA movement, serving as the country’s main armed forces during much of the Angolan Civil War.
 E902769 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: FAPLA | Statement: [MPLA, armedWing, FAPLA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: FAPLA
Context triple: [MPLA, armedWing, FAPLA]
  • A. FALA
    FALA is the ICAO airport code for Lanseria International Airport, a major privately owned international airport serving the Johannesburg region in South Africa.
  • B. FACA
    FACA is the commonly used acronym for the Federal Advisory Committee Act, a U.S. law that governs the operation and transparency of federal advisory committees.
  • C. FAPM
    FAPM is the ICAO airport code for Pietermaritzburg Airport in Pietermaritzburg, South Africa.
  • D. F.A.C.
    F.A.C. is the standard legal abbreviation used to refer to the Florida Administrative Code, which contains the administrative rules and regulations of the state of Florida.
  • E. AFA
    AFA is the Argentine Football Association, the main governing body responsible for organizing and regulating football in Argentina, including its national teams and professional leagues.
  • 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: FAPLA
Triple: [MPLA, armedWing, FAPLA]
Generated description
FAPLA was the military wing of Angola’s ruling MPLA movement, serving as the country’s main armed forces during much of the Angolan Civil War.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: FAPLA
Target entity description: FAPLA was the military wing of Angola’s ruling MPLA movement, serving as the country’s main armed forces during much of the Angolan Civil War.
  • A. FALA
    FALA is the ICAO airport code for Lanseria International Airport, a major privately owned international airport serving the Johannesburg region in South Africa.
  • B. FACA
    FACA is the commonly used acronym for the Federal Advisory Committee Act, a U.S. law that governs the operation and transparency of federal advisory committees.
  • C. FAPM
    FAPM is the ICAO airport code for Pietermaritzburg Airport in Pietermaritzburg, South Africa.
  • D. F.A.C.
    F.A.C. is the standard legal abbreviation used to refer to the Florida Administrative Code, which contains the administrative rules and regulations of the state of Florida.
  • E. AFA
    AFA is the Argentine Football Association, the main governing body responsible for organizing and regulating football in Argentina, including its national teams and professional leagues.
  • 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_69d6aa98650481908609c7c56bfa7902 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d798a4f3f88190a29710f64cef9d25 completed April 9, 2026, 12:16 p.m.
NED1 Entity disambiguation (via context triple) batch_69e3c87ab0308190a6a6ada1708f0ec2 completed April 18, 2026, 6:07 p.m.
NEDg Description generation batch_69e3cefc00148190a1850dc6e31523c3 completed April 18, 2026, 6:35 p.m.
NED2 Entity disambiguation (via description) batch_69e3d014a644819092c76aa02b573ca9 completed April 18, 2026, 6:40 p.m.
Created at: April 8, 2026, 9:26 p.m.