Triple

T4254023
Position Surface form Disambiguated ID Type / Status
Subject Pan American World Airways E95927 entity
Predicate IATAcode P418 FINISHED
Object PA
PA is the former IATA airline designator for Pan American World Airways, the pioneering and once-dominant U.S. international airline.
 E424329 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: PA | Statement: [Pan American World Airways, IATAcode, PA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: PA
Context triple: [Pan American World Airways, IATAcode, PA]
  • A. PA
    PA is the standard two-letter U.S. Postal Service abbreviation for the state of Pennsylvania.
  • B. PA
    PA is the postcode area in western Scotland that covers Paisley and parts of the surrounding Greater Glasgow region.
  • C. PA
    PA is the standard abbreviation for the Pakistan Army, the principal land warfare branch of Pakistan's armed forces.
  • D. PA
    The Palestinian Authority is an interim self-governing body established to administer parts of the West Bank and Gaza Strip as part of the Israeli-Palestinian peace process.
  • E. PAL
    PAL is the ICAO airline designator for Philippine Airlines, the flag carrier of the Philippines.
  • 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: PA
Triple: [Pan American World Airways, IATAcode, PA]
Generated description
PA is the former IATA airline designator for Pan American World Airways, the pioneering and once-dominant U.S. international airline.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: PA
Target entity description: PA is the former IATA airline designator for Pan American World Airways, the pioneering and once-dominant U.S. international airline.
  • A. PA
    PA is the standard two-letter U.S. Postal Service abbreviation for the state of Pennsylvania.
  • B. PA
    PA is the postcode area in western Scotland that covers Paisley and parts of the surrounding Greater Glasgow region.
  • C. PA
    The Palestinian Authority is an interim self-governing body established to administer parts of the West Bank and Gaza Strip as part of the Israeli-Palestinian peace process.
  • D. PA
    PA is the standard abbreviation for the Pakistan Army, the principal land warfare branch of Pakistan's armed forces.
  • E. PAL
    PAL is the ICAO airline designator for Philippine Airlines, the flag carrier of the Philippines.
  • 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_69b3453f759881909b91f01a1e82c036 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b34ebe6fbc8190a89269b478b3f435 completed March 12, 2026, 11:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5a887703c81909a40f23f83154b8c completed March 14, 2026, 6:27 p.m.
NEDg Description generation batch_69b5a8ffd4508190b33117d3fc963b3d completed March 14, 2026, 6:29 p.m.
NED2 Entity disambiguation (via description) batch_69b5a9754d5c8190b1ab724a4758c22a completed March 14, 2026, 6:31 p.m.
Created at: March 12, 2026, 11:06 p.m.