Triple

T6894586
Position Surface form Disambiguated ID Type / Status
Subject Xiamen Gaoqi International Airport E159139 entity
Predicate IATAcode P418 FINISHED
Object XMN
XMN is the IATA airport code for Xiamen Gaoqi International Airport, the main air gateway serving Xiamen in Fujian Province, China.
 E626729 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: XMN | Statement: [Xiamen Gaoqi International Airport, IATAcode, XMN]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: XMN
Context triple: [Xiamen Gaoqi International Airport, IATAcode, XMN]
  • A. CNXMN
    CNXMN is the UN/LOCODE identifier for the Port of Xiamen, a major seaport and shipping hub in southeastern China.
  • B. XNM
    XNM is the IATA airport-style code assigned to Norwich railway station in Norwich, England, for use in integrated transport and ticketing systems.
  • C. BXM
    BXM is the railway station code for Brussels-South (Bruxelles-Midi / Brussel-Zuid), the main international and domestic rail hub in Brussels, Belgium.
  • D. XU
    XU was a clandestine Norwegian intelligence organization that gathered and transmitted vital information to the Allies during the German occupation in World War II.
  • E. XZN
    XZN is the IATA station code assigned to the Avignon TGV high-speed railway station in southeastern France.
  • 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: XMN
Triple: [Xiamen Gaoqi International Airport, IATAcode, XMN]
Generated description
XMN is the IATA airport code for Xiamen Gaoqi International Airport, the main air gateway serving Xiamen in Fujian Province, China.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: XMN
Target entity description: XMN is the IATA airport code for Xiamen Gaoqi International Airport, the main air gateway serving Xiamen in Fujian Province, China.
  • A. CNXMN
    CNXMN is the UN/LOCODE identifier for the Port of Xiamen, a major seaport and shipping hub in southeastern China.
  • B. XNM
    XNM is the IATA airport-style code assigned to Norwich railway station in Norwich, England, for use in integrated transport and ticketing systems.
  • C. BXM
    BXM is the railway station code for Brussels-South (Bruxelles-Midi / Brussel-Zuid), the main international and domestic rail hub in Brussels, Belgium.
  • D. XU
    XU was a clandestine Norwegian intelligence organization that gathered and transmitted vital information to the Allies during the German occupation in World War II.
  • E. XZN
    XZN is the IATA station code assigned to the Avignon TGV high-speed railway station in southeastern France.
  • 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_69c6883568c8819081db6407e892cccc completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d931da24819096b9b205f2c0ebb0 completed March 27, 2026, 7:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69c748db2bd48190bb26f60c58ec8229 completed March 28, 2026, 3:19 a.m.
NEDg Description generation batch_69c749901de081908e5c3ccd324e8191 completed March 28, 2026, 3:22 a.m.
NED2 Entity disambiguation (via description) batch_69c74a0bcddc819084b22925cf57a205 completed March 28, 2026, 3:24 a.m.
Created at: March 27, 2026, 2:24 p.m.