Triple

T13366829
Position Surface form Disambiguated ID Type / Status
Subject Vance Brand Airport E318960 entity
Predicate IATA code P2569 FINISHED
Object LMO
LMO is the IATA airport code for Vance Brand Airport, a public general aviation facility serving Longmont, Colorado.
 E1037665 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: LMO | Statement: [Vance Brand Airport, IATA code, LMO]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: LMO
Context triple: [Vance Brand Airport, IATA code, LMO]
  • A. LMO
    LMO is the IATA airport code for RAF Lossiemouth, a Royal Air Force station and military airfield in Moray, Scotland.
  • B. LOM
    LOM is the official abbreviation for the Legion of Merit, a prestigious United States military decoration awarded for exceptionally meritorious conduct in the performance of outstanding services and achievements.
  • C. lom
    lom is the ISO 639-3 language code for the Loma language spoken primarily in Liberia and neighboring West African regions.
  • D. Lom
    Lom is a mountainous municipality in Innlandet county, Norway, known for its historic stave church and as a gateway to the Jotunheimen National Park.
  • E. LÖ
    LÖ is the vehicle registration code for the district of Lörrach in the German state of Baden-Württemberg.
  • 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: LMO
Triple: [Vance Brand Airport, IATA code, LMO]
Generated description
LMO is the IATA airport code for Vance Brand Airport, a public general aviation facility serving Longmont, Colorado.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: LMO
Target entity description: LMO is the IATA airport code for Vance Brand Airport, a public general aviation facility serving Longmont, Colorado.
  • A. LMO
    LMO is the IATA airport code for RAF Lossiemouth, a Royal Air Force station and military airfield in Moray, Scotland.
  • B. LOM
    LOM is the official abbreviation for the Legion of Merit, a prestigious United States military decoration awarded for exceptionally meritorious conduct in the performance of outstanding services and achievements.
  • C. lom
    lom is the ISO 639-3 language code for the Loma language spoken primarily in Liberia and neighboring West African regions.
  • D. Lom
    Lom is a mountainous municipality in Innlandet county, Norway, known for its historic stave church and as a gateway to the Jotunheimen National Park.
  • E. LÖ
    LÖ is the vehicle registration code for the district of Lörrach in the German state of Baden-Württemberg.
  • 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_69d806b7bbac8190b85278c87fa7aff3 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69dadcd652d48190a782fd1f57f34b6a completed April 11, 2026, 11:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69f72680df088190b8dbcc8ad0d7366e completed May 3, 2026, 10:42 a.m.
NEDg Description generation batch_69f727512c94819091985c7942f40b31 completed May 3, 2026, 10:45 a.m.
NED2 Entity disambiguation (via description) batch_69f72b77d650819092c02f6488b2cfb2 completed May 3, 2026, 11:03 a.m.
Created at: April 9, 2026, 9:32 p.m.