Triple

T9631058
Position Surface form Disambiguated ID Type / Status
Subject RAF Lossiemouth E232803 entity
Predicate IATACode P418 FINISHED
Object LMO
LMO is the IATA airport code for RAF Lossiemouth, a Royal Air Force station and military airfield in Moray, Scotland.
 E812065 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: [RAF Lossiemouth, IATACode, LMO]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: LMO
Context triple: [RAF Lossiemouth, IATACode, LMO]
  • A. 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.
  • B. 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.
  • C. LÖ
    LÖ is the vehicle registration code for the district of Lörrach in the German state of Baden-Württemberg.
  • D. Lm
    Lm is the currency symbol that was used to denote the Maltese lira, Malta’s former national currency before adoption of the euro.
  • E. LMA
    LMA is the League Managers Association, the professional body representing and supporting football managers in English 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: LMO
Triple: [RAF Lossiemouth, IATACode, LMO]
Generated description
LMO is the IATA airport code for RAF Lossiemouth, a Royal Air Force station and military airfield in Moray, Scotland.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: LMO
Target entity description: LMO is the IATA airport code for RAF Lossiemouth, a Royal Air Force station and military airfield in Moray, Scotland.
  • A. 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.
  • B. 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.
  • C. LÖ
    LÖ is the vehicle registration code for the district of Lörrach in the German state of Baden-Württemberg.
  • D. Lm
    Lm is the currency symbol that was used to denote the Maltese lira, Malta’s former national currency before adoption of the euro.
  • E. LMA
    LMA is the League Managers Association, the professional body representing and supporting football managers in English 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_69ca848940cc8190b97cec654cb3bb4a completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd9b2621408190bfe2ea5a05359ee0 completed April 1, 2026, 10:24 p.m.
NED1 Entity disambiguation (via context triple) batch_69d1822e12b8819089d4a64a9980cfcd completed April 4, 2026, 9:27 p.m.
NEDg Description generation batch_69d183c71a44819092f556c8b1301fca completed April 4, 2026, 9:33 p.m.
NED2 Entity disambiguation (via description) batch_69d1842ba7088190bc663ede36b2d396 completed April 4, 2026, 9:35 p.m.
Created at: March 30, 2026, 8:11 p.m.