Triple

T4199430
Position Surface form Disambiguated ID Type / Status
Subject Léopold Sédar Senghor International Airport E86030 entity
Predicate IATAcode P418 FINISHED
Object DKR
DKR is the IATA airport code for Léopold Sédar Senghor International Airport, the former main international gateway to Dakar, Senegal.
 E420453 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: DKR | Statement: [Léopold Sédar Senghor International Airport, IATAcode, DKR]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: DKR
Context triple: [Léopold Sédar Senghor International Airport, IATAcode, DKR]
  • A. DK
    DK is a British illustrated reference publisher best known for its highly visual nonfiction books for children and adults across topics like science, history, travel, and nature.
  • B. DK
    DK is the ISO 3166-1 alpha-2 country code for Denmark, a Nordic nation in Northern Europe.
  • C. DK
    DK is the standard scholarly abbreviation for the Diels–Kranz collection of pre-Socratic Greek philosophical fragments.
  • D. RKR
    RKR is the vehicle registration code assigned to vehicles registered in the Rymanów area of Poland.
  • E. DKS
    DKS is the stock ticker symbol for Dick's Sporting Goods, a major U.S. retail chain specializing in sporting goods and outdoor equipment.
  • 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: DKR
Triple: [Léopold Sédar Senghor International Airport, IATAcode, DKR]
Generated description
DKR is the IATA airport code for Léopold Sédar Senghor International Airport, the former main international gateway to Dakar, Senegal.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: DKR
Target entity description: DKR is the IATA airport code for Léopold Sédar Senghor International Airport, the former main international gateway to Dakar, Senegal.
  • A. DK
    DK is a British illustrated reference publisher best known for its highly visual nonfiction books for children and adults across topics like science, history, travel, and nature.
  • B. DK
    DK is the ISO 3166-1 alpha-2 country code for Denmark, a Nordic nation in Northern Europe.
  • C. DK
    DK is the standard scholarly abbreviation for the Diels–Kranz collection of pre-Socratic Greek philosophical fragments.
  • D. RKR
    RKR is the vehicle registration code assigned to vehicles registered in the Rymanów area of Poland.
  • E. DKS
    DKS is the stock ticker symbol for Dick's Sporting Goods, a major U.S. retail chain specializing in sporting goods and outdoor equipment.
  • 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_69aed93b89f48190a31f6d57c760e42f completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69af036243b4819097efe6b796823cd9 completed March 9, 2026, 5:29 p.m.
NED1 Entity disambiguation (via context triple) batch_69b58a12c11481908033229ecf90c9f9 completed March 14, 2026, 4:17 p.m.
NEDg Description generation batch_69b58e053adc8190909d92de845dd6df completed March 14, 2026, 4:34 p.m.
NED2 Entity disambiguation (via description) batch_69b58f219a708190af631335027532e3 completed March 14, 2026, 4:38 p.m.
Created at: March 9, 2026, 3:49 p.m.