Triple

T22553221
Position Surface form Disambiguated ID Type / Status
Subject Flimby railway station E557611 entity
Predicate stationCode P1289 FINISHED
Object FLM
FLM is the National Rail station code for Flimby railway station in Cumbria, England.
 E1542612 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: FLM | Statement: [Flimby railway station, stationCode, FLM]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: FLM
Context triple: [Flimby railway station, stationCode, FLM]
  • A. FLMF
    FLMF is the ICAO airport code for Mfuwe Airport in Zambia, which serves as a key gateway to the South Luangwa National Park.
  • B. FLI
    FLI is Germany’s national research institute for animal health, focusing on the study and control of infectious diseases in livestock and other animals.
  • C. FMV
    FMV is the Swedish Defence Materiel Administration, the government agency responsible for procuring and managing equipment and systems for Sweden’s armed forces.
  • D. LFMV
    LFMV is the ICAO airport code for Avignon – Provence Airport in southeastern France.
  • E. FLS
    FLS is the station code for Flushing–Main Street, a major Long Island Rail Road terminal in Queens, New York City.
  • 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: FLM
Triple: [Flimby railway station, stationCode, FLM]
Generated description
FLM is the National Rail station code for Flimby railway station in Cumbria, England.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: FLM
Target entity description: FLM is the National Rail station code for Flimby railway station in Cumbria, England.
  • A. FLMF
    FLMF is the ICAO airport code for Mfuwe Airport in Zambia, which serves as a key gateway to the South Luangwa National Park.
  • B. FLI
    FLI is Germany’s national research institute for animal health, focusing on the study and control of infectious diseases in livestock and other animals.
  • C. FMV
    FMV is the Swedish Defence Materiel Administration, the government agency responsible for procuring and managing equipment and systems for Sweden’s armed forces.
  • D. LFMV
    LFMV is the ICAO airport code for Avignon – Provence Airport in southeastern France.
  • E. FLS
    FLS is the station code for Flushing–Main Street, a major Long Island Rail Road terminal in Queens, New York City.
  • 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_69e11e59db848190b4272ecd2b690ffd completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f15f775d308190b35a52310e9c84f7 completed April 29, 2026, 1:31 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0b2d6510648190aba36f0ad1bb4f81 completed May 18, 2026, 3:16 p.m.
NEDg Description generation batch_6a0b364718308190937c3b7ae90ea9df completed May 18, 2026, 3:54 p.m.
NED2 Entity disambiguation (via description) batch_6a0b37998f888190bb53c2429760321a completed May 18, 2026, 4 p.m.
Created at: April 16, 2026, 8:52 p.m.