Triple

T14996647
Position Surface form Disambiguated ID Type / Status
Subject Lanzhou Zhongchuan International Airport E373974 entity
Predicate ICAOcode P419 FINISHED
Object ZLLL
ZLLL is the ICAO airport code for Lanzhou Zhongchuan International Airport, a major air transport hub serving Lanzhou and the surrounding region in Gansu Province, China.
 E1130945 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: ZLLL | Statement: [Lanzhou Zhongchuan International Airport, ICAOcode, ZLLL]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: ZLLL
Context triple: [Lanzhou Zhongchuan International Airport, ICAOcode, ZLLL]
  • A. LZZ
    LZZ is the station code used to identify Liuzhou railway station in China’s railway network.
  • B. ZL
    ZL is the IATA airline designator used by Rex Airlines, a regional carrier based in Australia.
  • C. ZL
    ZL is the official station code used to identify Zwolle railway station in the Netherlands’ rail network.
  • D. ZVVZ
    ZVVZ is a Czech industrial company known for producing air-handling, filtration, and environmental technology equipment.
  • E. ZLW
    ZLW is the National Rail station code assigned to Whitechapel railway station in London.
  • 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: ZLLL
Triple: [Lanzhou Zhongchuan International Airport, ICAOcode, ZLLL]
Generated description
ZLLL is the ICAO airport code for Lanzhou Zhongchuan International Airport, a major air transport hub serving Lanzhou and the surrounding region in Gansu Province, China.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: ZLLL
Target entity description: ZLLL is the ICAO airport code for Lanzhou Zhongchuan International Airport, a major air transport hub serving Lanzhou and the surrounding region in Gansu Province, China.
  • A. LZZ
    LZZ is the station code used to identify Liuzhou railway station in China’s railway network.
  • B. ZL
    ZL is the IATA airline designator used by Rex Airlines, a regional carrier based in Australia.
  • C. ZL
    ZL is the official station code used to identify Zwolle railway station in the Netherlands’ rail network.
  • D. ZVVZ
    ZVVZ is a Czech industrial company known for producing air-handling, filtration, and environmental technology equipment.
  • E. ZLW
    ZLW is the National Rail station code assigned to Whitechapel railway station in London.
  • 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_69d85ccc84388190aa151e5173370c8d completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69ded718e4288190b5e144f82299a194 completed April 15, 2026, 12:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69fe969c3ba88190899f06b185e94ccf completed May 9, 2026, 2:06 a.m.
NEDg Description generation batch_69fe972728dc8190a9cf2a3e984b05a7 completed May 9, 2026, 2:08 a.m.
NED2 Entity disambiguation (via description) batch_69fe9790d1d081908fc94829d3104e07 completed May 9, 2026, 2:10 a.m.
Created at: April 10, 2026, 2:53 a.m.