Triple

T16583967
Position Surface form Disambiguated ID Type / Status
Subject Huangshan Tunxi International Airport E402905 entity
Predicate IATAcode P418 FINISHED
Object TXN
TXN is the IATA airport code for Huangshan Tunxi International Airport, serving the Huangshan (Yellow Mountain) region in Anhui, China.
 E1220969 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: TXN | Statement: [Huangshan Tunxi International Airport, IATAcode, TXN]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: TXN
Context triple: [Huangshan Tunxi International Airport, IATAcode, TXN]
  • A. TXN
    TXN is the stock ticker symbol for Texas Instruments Incorporated, a major American technology company known for designing and manufacturing semiconductors and integrated circuits.
  • B. TXK
    TXK is the IATA airport code for Texarkana Regional Airport, which serves the Texarkana area in Texas and Arkansas.
  • C. TXP
    TXP is the station code used to identify Tianjin West Railway Station in China’s railway network.
  • D. TxTag
    TxTag is an electronic toll collection system used on Texas toll roads that allows drivers to pay tolls automatically without stopping.
  • E. TXL
    TXL was the IATA airport code for Berlin Tegel Airport, the former main international airport of Berlin, Germany.
  • 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: TXN
Triple: [Huangshan Tunxi International Airport, IATAcode, TXN]
Generated description
TXN is the IATA airport code for Huangshan Tunxi International Airport, serving the Huangshan (Yellow Mountain) region in Anhui, China.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: TXN
Target entity description: TXN is the IATA airport code for Huangshan Tunxi International Airport, serving the Huangshan (Yellow Mountain) region in Anhui, China.
  • A. TXN
    TXN is the stock ticker symbol for Texas Instruments Incorporated, a major American technology company known for designing and manufacturing semiconductors and integrated circuits.
  • B. TXK
    TXK is the IATA airport code for Texarkana Regional Airport, which serves the Texarkana area in Texas and Arkansas.
  • C. TXP
    TXP is the station code used to identify Tianjin West Railway Station in China’s railway network.
  • D. TxTag
    TxTag is an electronic toll collection system used on Texas toll roads that allows drivers to pay tolls automatically without stopping.
  • E. TXL
    TXL was the IATA airport code for Berlin Tegel Airport, the former main international airport of Berlin, Germany.
  • 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_69d88387363c8190a97a0c942130de97 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e35999f80c8190852fd4137bc45a80 completed April 18, 2026, 10:14 a.m.
NED1 Entity disambiguation (via context triple) batch_6a006ef2d6048190954144ab848760ec completed May 10, 2026, 11:41 a.m.
NEDg Description generation batch_6a006fc84390819083d9d2ac1c558827 completed May 10, 2026, 11:45 a.m.
NED2 Entity disambiguation (via description) batch_6a007068715c8190914ccac7b14103e4 completed May 10, 2026, 11:47 a.m.
Created at: April 10, 2026, 5:16 a.m.