Triple

T18609593
Position Surface form Disambiguated ID Type / Status
Subject West Memphis Municipal Airport E454855 entity
Predicate faaLid P420 FINISHED
Object AWM
AWM is the FAA location identifier for West Memphis Municipal Airport in Arkansas, United States.
 E1333753 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: AWM | Statement: [West Memphis Municipal Airport, faaLid, AWM]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: AWM
Context triple: [West Memphis Municipal Airport, faaLid, AWM]
  • A. AWC
    AWC is the U.S. Aviation Weather Center, a National Weather Service unit that provides critical weather forecasts and warnings for aviation safety.
  • B. AMA
    AMA is the three-letter IATA airport code for Rick Husband Amarillo International Airport in Amarillo, Texas.
  • C. AMA
    AMA is the commonly used abbreviation for Japan’s Antimonopoly Act, the core law regulating competition and prohibiting monopolistic practices in the country.
  • D. AMA
    AMA is the leading professional association and lobbying group representing physicians and medical students in the United States.
  • E. AWA
    AWA is the commonly used abbreviation for the Animal Welfare Act, the primary U.S. federal law regulating the treatment of animals in research, exhibition, transport, and by dealers.
  • 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: AWM
Triple: [West Memphis Municipal Airport, faaLid, AWM]
Generated description
AWM is the FAA location identifier for West Memphis Municipal Airport in Arkansas, United States.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: AWM
Target entity description: AWM is the FAA location identifier for West Memphis Municipal Airport in Arkansas, United States.
  • A. AWC
    AWC is the U.S. Aviation Weather Center, a National Weather Service unit that provides critical weather forecasts and warnings for aviation safety.
  • B. AMA
    AMA is the three-letter IATA airport code for Rick Husband Amarillo International Airport in Amarillo, Texas.
  • C. AMA
    AMA is the commonly used abbreviation for Japan’s Antimonopoly Act, the core law regulating competition and prohibiting monopolistic practices in the country.
  • D. AMA
    AMA is the leading professional association and lobbying group representing physicians and medical students in the United States.
  • E. AWA
    AWA is the commonly used abbreviation for the Animal Welfare Act, the primary U.S. federal law regulating the treatment of animals in research, exhibition, transport, and by dealers.
  • 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_69d8d38bbe7c8190bdec3138e7d413c9 completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e54d0048b08190a7dd407f14d95799 completed April 19, 2026, 9:45 p.m.
NED1 Entity disambiguation (via context triple) batch_6a050387fe1c8190b29d4f4ad6ec4d6e completed May 13, 2026, 11:04 p.m.
NEDg Description generation batch_6a0504a2ee3081908fd92ea5ace4f62c completed May 13, 2026, 11:09 p.m.
NED2 Entity disambiguation (via description) batch_6a0505048ad081908ae23163a71a3c17 completed May 13, 2026, 11:11 p.m.
Created at: April 10, 2026, 11:45 a.m.