Triple

T2069918
Position Surface form Disambiguated ID Type / Status
Subject Copa Airlines E45992 entity
Predicate callsign P1565 FINISHED
Object COPA
COPA is the airline callsign used by Copa Airlines, the flag carrier of Panama known for its extensive network across the Americas.
 E230976 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: COPA | Statement: [Copa Airlines, callsign, COPA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: COPA
Context triple: [Copa Airlines, callsign, COPA]
  • A. COPA
    COPA is an independent Chicago city agency responsible for investigating allegations of police misconduct and promoting police accountability.
  • B. COP
    COP is the official currency code used internationally to represent the Colombian peso.
  • C. COP
    COP is the main annual United Nations climate summit where countries negotiate global agreements to address climate change.
  • D. UNCAF
    UNCAF is the Central American Football Union, the regional governing body for association football in Central America under CONCACAF.
  • E. NCOP
    NCOP is South Africa’s upper house of Parliament, representing the country’s nine provinces in the national legislative process.
  • 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: COPA
Triple: [Copa Airlines, callsign, COPA]
Generated description
COPA is the airline callsign used by Copa Airlines, the flag carrier of Panama known for its extensive network across the Americas.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: COPA
Target entity description: COPA is the airline callsign used by Copa Airlines, the flag carrier of Panama known for its extensive network across the Americas.
  • A. COPA
    COPA is an independent Chicago city agency responsible for investigating allegations of police misconduct and promoting police accountability.
  • B. COP
    COP is the official currency code used internationally to represent the Colombian peso.
  • C. COP
    COP is the main annual United Nations climate summit where countries negotiate global agreements to address climate change.
  • D. UNCAF
    UNCAF is the Central American Football Union, the regional governing body for association football in Central America under CONCACAF.
  • E. NCOP
    NCOP is South Africa’s upper house of Parliament, representing the country’s nine provinces in the national legislative process.
  • 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_69a8891b38288190abd572ccad9b6928 completed March 4, 2026, 7:33 p.m.
NER Named-entity recognition batch_69abb9f677108190aea3c8db7850c892 completed March 7, 2026, 5:39 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae27289eb081909bfbc9bf2cd14878 completed March 9, 2026, 1:49 a.m.
NEDg Description generation batch_69ae28c163088190818891302f7faa8e completed March 9, 2026, 1:56 a.m.
NED2 Entity disambiguation (via description) batch_69ae292a9d7481909acbc3a5f24ff0b9 completed March 9, 2026, 1:58 a.m.
Created at: March 4, 2026, 7:41 p.m.