Triple

T875057
Position Surface form Disambiguated ID Type / Status
Subject Stockholm Arlanda Airport E18898 entity
Predicate IATAcode P418 FINISHED
Object ARN
ARN is the three-letter IATA airport code for Stockholm Arlanda Airport, the main international gateway to Stockholm and one of Sweden’s busiest airports.
 E103982 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: ARN | Statement: [Stockholm Arlanda Airport, IATAcode, ARN]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: ARN
Context triple: [Stockholm Arlanda Airport, IATAcode, ARN]
  • A. AN
    AN is the vehicle registration code used on license plates for the Ansbach district in the Middle Franconia region of Bavaria, Germany.
  • B. ARC
    ARC is the commonly used acronym for the Augmentation Research Center, a pioneering research group known for its early work on interactive computing and human–computer interaction.
  • C. AR
    AR is the standard abbreviation for the Romanian Academy, the leading national institution for the promotion of science, culture, and the arts in Romania.
  • D. AR
    AR is the commonly used abbreviation for the Assembly of the Republic, the unicameral national parliament of Portugal.
  • E. AAR
    AAR is the American Association of Railroads' wheel arrangement classification system commonly used to describe locomotive axle configurations in North America.
  • 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: ARN
Triple: [Stockholm Arlanda Airport, IATAcode, ARN]
Generated description
ARN is the three-letter IATA airport code for Stockholm Arlanda Airport, the main international gateway to Stockholm and one of Sweden’s busiest airports.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: ARN
Target entity description: ARN is the three-letter IATA airport code for Stockholm Arlanda Airport, the main international gateway to Stockholm and one of Sweden’s busiest airports.
  • A. AN
    AN is the vehicle registration code used on license plates for the Ansbach district in the Middle Franconia region of Bavaria, Germany.
  • B. ARC
    ARC is the commonly used acronym for the Augmentation Research Center, a pioneering research group known for its early work on interactive computing and human–computer interaction.
  • C. AR
    AR is the standard abbreviation for the Romanian Academy, the leading national institution for the promotion of science, culture, and the arts in Romania.
  • D. AR
    AR is the commonly used abbreviation for the Assembly of the Republic, the unicameral national parliament of Portugal.
  • E. AAR
    AAR is the American Association of Railroads' wheel arrangement classification system commonly used to describe locomotive axle configurations in North America.
  • 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_69a4938db1f081909bcd1ad2713b6096 completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4acae12948190923d31966c26a130 completed March 1, 2026, 9:16 p.m.
NED1 Entity disambiguation (via context triple) batch_69a7b8520a008190a15bdb93e8ce2438 completed March 4, 2026, 4:42 a.m.
NEDg Description generation batch_69a7b9774df881908fbd4d1b54442cdc completed March 4, 2026, 4:47 a.m.
NED2 Entity disambiguation (via description) batch_69a7ba46a2ec8190892404cb1f259cf0 completed March 4, 2026, 4:51 a.m.
Created at: March 1, 2026, 7:39 p.m.