Triple

T12617999
Position Surface form Disambiguated ID Type / Status
Subject Memmingen E301302 entity
Predicate airportIATAcode P418 FINISHED
Object FMM
FMM is the IATA airport code for Memmingen Airport, a regional international airport in southern Germany often used as a low-cost alternative to Munich.
E992104 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: FMM | Statement: [Memmingen, airportIATAcode, FMM]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: FMM
Context triple: [Memmingen, airportIATAcode, FMM]
  • A. FMM Sines
    FMM Sines is a renowned world music festival held annually in Sines, Portugal, showcasing diverse global artists and musical traditions.
  • B. FFM
    FFM is an abbreviation commonly used for the Montreal World Film Festival, an international film festival held annually in Montreal, Canada.
  • C. FMF
    FMF is the commonly used abbreviation for the Mexican Football Federation, the governing body of professional and amateur soccer in Mexico.
  • D. FMF
    FMF is a U.S. government program that provides grants and loans to help foreign countries purchase American defense equipment, services, and training.
  • E. FPM
    FPM is the Fellow Programme in Management, a doctoral-level research program in management studies offered by the Indian Institutes of Management.
  • 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: FMM
Triple: [Memmingen, airportIATAcode, FMM]
Generated description
FMM is the IATA airport code for Memmingen Airport, a regional international airport in southern Germany often used as a low-cost alternative to Munich.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: FMM
Target entity description: FMM is the IATA airport code for Memmingen Airport, a regional international airport in southern Germany often used as a low-cost alternative to Munich.
  • A. FMM Sines
    FMM Sines is a renowned world music festival held annually in Sines, Portugal, showcasing diverse global artists and musical traditions.
  • B. FFM
    FFM is an abbreviation commonly used for the Montreal World Film Festival, an international film festival held annually in Montreal, Canada.
  • C. FMF
    FMF is the commonly used abbreviation for the Mexican Football Federation, the governing body of professional and amateur soccer in Mexico.
  • D. FMF
    FMF is a U.S. government program that provides grants and loans to help foreign countries purchase American defense equipment, services, and training.
  • E. FPM
    FPM is the Fellow Programme in Management, a doctoral-level research program in management studies offered by the Indian Institutes of Management.
  • 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_69d7bdeaf49c8190b13800111fa77ea3 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d960c63ea48190ae1aae9280a023a6 completed April 10, 2026, 8:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69f65ed507988190b9d46586f3c3584c completed May 2, 2026, 8:30 p.m.
NEDg Description generation batch_69f65fb03b248190b264230b84b17635 completed May 2, 2026, 8:33 p.m.
NED2 Entity disambiguation (via description) batch_69f6608ec32c8190803c6f5677c300d6 completed May 2, 2026, 8:37 p.m.
Created at: April 9, 2026, 5:13 p.m.