Triple

T15196617
Position Surface form Disambiguated ID Type / Status
Subject Malmö Airport E363152 entity
Predicate ICAOcode P419 FINISHED
Object ESMS
ESMS is the ICAO airport code for Malmö Airport, an international airport serving the Malmö region in southern Sweden.
E1143315 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: ESMS | Statement: [Malmö Airport, ICAOcode, ESMS]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: ESMS
Context triple: [Malmö Airport, ICAOcode, ESMS]
  • A. ESMX
    ESMX is the ICAO airport code for Växjö Småland Airport in southern Sweden.
  • B. SMSE
    SMSE is the Shiley-Marcos School of Engineering, an academic division focused on engineering education and research at the University of San Diego.
  • C. MES
    MES is the former IATA airport code that was used for Polonia International Airport in Medan, Indonesia.
  • D. EMS
    EMS is an emergency medical services organization that provides pre-hospital care and ambulance transport in response to medical emergencies.
  • E. EMS
    EMS is the vehicle registration code used on license plates for vehicles registered in the district of Rhein-Lahn-Kreis, whose administrative seat is Nassau, in the German state of Rhineland-Palatinate.
  • 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: ESMS
Triple: [Malmö Airport, ICAOcode, ESMS]
Generated description
ESMS is the ICAO airport code for Malmö Airport, an international airport serving the Malmö region in southern Sweden.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: ESMS
Target entity description: ESMS is the ICAO airport code for Malmö Airport, an international airport serving the Malmö region in southern Sweden.
  • A. ESMX
    ESMX is the ICAO airport code for Växjö Småland Airport in southern Sweden.
  • B. SMSE
    SMSE is the Shiley-Marcos School of Engineering, an academic division focused on engineering education and research at the University of San Diego.
  • C. MES
    MES is the former IATA airport code that was used for Polonia International Airport in Medan, Indonesia.
  • D. EMS
    EMS is an emergency medical services organization that provides pre-hospital care and ambulance transport in response to medical emergencies.
  • E. EMS
    EMS is a Christian mission organization focused on international partnership, evangelism, and social justice work, particularly within the global evangelical community.
  • 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_69d85a0b78bc8190b6e5ad51a2c4cfc5 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e0067fcc788190abdc083d4eadeb36 completed April 15, 2026, 9:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69fed3324fdc8190b31d4d2fcaffc57a completed May 9, 2026, 6:24 a.m.
NEDg Description generation batch_69fed44b2e3c8190aad111e2bc2b56a2 completed May 9, 2026, 6:29 a.m.
NED2 Entity disambiguation (via description) batch_69fed547192c8190b89755fff48ca620 completed May 9, 2026, 6:33 a.m.
Created at: April 10, 2026, 3:10 a.m.