Triple

T3552740
Position Surface form Disambiguated ID Type / Status
Subject KLM Cityhopper E75146 entity
Predicate IATACode P418 FINISHED
Object WA
WA is the IATA airline designator assigned to KLM Cityhopper, the regional subsidiary of KLM Royal Dutch Airlines.
 E367003 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: WA | Statement: [KLM Cityhopper, IATACode, WA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: WA
Context triple: [KLM Cityhopper, IATACode, WA]
  • A. WA
    WA is the vehicle registration code used on license plates for cars registered in Warsaw, the capital city of Poland.
  • B. WA
    WA is a UK postcode area covering parts of Warrington and surrounding towns in northwest England.
  • C. Washington
    Washington is a U.S. state in the Pacific Northwest known for its diverse landscapes, technology industry centered around Seattle, and significant cultural and economic influence on the West Coast.
  • D. Washington
    Washington is a small town in Dutchess County, New York, known for its rural character and the village of Millbrook within its borders.
  • E. Washington
    Washington is a common English surname most famously borne by George Washington, the first president of the United States.
  • 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: WA
Triple: [KLM Cityhopper, IATACode, WA]
Generated description
WA is the IATA airline designator assigned to KLM Cityhopper, the regional subsidiary of KLM Royal Dutch Airlines.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: WA
Target entity description: WA is the IATA airline designator assigned to KLM Cityhopper, the regional subsidiary of KLM Royal Dutch Airlines.
  • A. WA
    WA is the vehicle registration code used on license plates for cars registered in Warsaw, the capital city of Poland.
  • B. WA
    WA is a UK postcode area covering parts of Warrington and surrounding towns in northwest England.
  • C. Washington
    Washington is a small rural town in Berkshire County in western Massachusetts, known for its forested landscape and quiet, sparsely populated character.
  • D. Washington
    Washington is a U.S. state in the Pacific Northwest known for its diverse landscapes, technology industry centered around Seattle, and significant cultural and economic influence on the West Coast.
  • E. Washington
    Washington is a small town in Dutchess County, New York, known for its rural character and the village of Millbrook within its borders.
  • 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_69ad85d33c6c819081d5ac1df13b5680 completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc05394888190b59fafda97b49beb completed March 8, 2026, 6:30 p.m.
NED1 Entity disambiguation (via context triple) batch_69b38beef8b4819090109ab89e9671d6 completed March 13, 2026, 4 a.m.
NEDg Description generation batch_69b38c84fc788190a074f14a76bb7944 completed March 13, 2026, 4:03 a.m.
NED2 Entity disambiguation (via description) batch_69b38cb872948190a75bc6d6829187c5 completed March 13, 2026, 4:04 a.m.
Created at: March 8, 2026, 3:20 p.m.