Triple

T5731278
Position Surface form Disambiguated ID Type / Status
Subject Kualanamu International Airport E126388 entity
Predicate ICAOcode P419 FINISHED
Object WIMM
WIMM is the ICAO airport code for Kualanamu International Airport, a major airport serving Medan and the surrounding region in North Sumatra, Indonesia.
E539466 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: WIMM | Statement: [Kualanamu International Airport, ICAOcode, WIMM]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: WIMM
Context triple: [Kualanamu International Airport, ICAOcode, WIMM]
  • A. WIMK
    WIMK is the former ICAO airport code once assigned to Polonia International Airport in Indonesia.
  • B. WMI
    WMI is the IATA airport code for Warsaw Modlin Airport, a secondary international airport serving the Warsaw metropolitan area in Poland.
  • C. WLM
    WLM (Workload Manager) is an IBM z/OS component that dynamically manages and prioritizes system workloads to meet performance goals and service-level objectives.
  • D. WID
    WID is the National Rail station code assigned to Widnes railway station in Cheshire, England.
  • E. WAMO
    WAMO is a Pittsburgh-area radio station historically known for its urban contemporary and hip-hop programming serving the region’s Black community.
  • 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: WIMM
Triple: [Kualanamu International Airport, ICAOcode, WIMM]
Generated description
WIMM is the ICAO airport code for Kualanamu International Airport, a major airport serving Medan and the surrounding region in North Sumatra, Indonesia.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: WIMM
Target entity description: WIMM is the ICAO airport code for Kualanamu International Airport, a major airport serving Medan and the surrounding region in North Sumatra, Indonesia.
  • A. WIMK
    WIMK is the former ICAO airport code once assigned to Polonia International Airport in Indonesia.
  • B. WMI
    WMI is the IATA airport code for Warsaw Modlin Airport, a secondary international airport serving the Warsaw metropolitan area in Poland.
  • C. WLM
    WLM (Workload Manager) is an IBM z/OS component that dynamically manages and prioritizes system workloads to meet performance goals and service-level objectives.
  • D. WID
    WID is the National Rail station code assigned to Widnes railway station in Cheshire, England.
  • E. WAMO
    WAMO is a Pittsburgh-area radio station historically known for its urban contemporary and hip-hop programming serving the region’s Black 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_69c0083082288190b7478cead6b5430a completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c025318d688190bd878c5aa1a28728 completed March 22, 2026, 5:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69c05a906e008190bd2b9a3481733f14 completed March 22, 2026, 9:09 p.m.
NEDg Description generation batch_69c05cabceac819095c4a114220efb1a completed March 22, 2026, 9:18 p.m.
NED2 Entity disambiguation (via description) batch_69c05d30463481909876ca02516d31cc completed March 22, 2026, 9:20 p.m.
Created at: March 22, 2026, 3:47 p.m.