Triple

T5263788
Position Surface form Disambiguated ID Type / Status
Subject Hannover Airport E118889 entity
Predicate hasRunway P105 FINISHED
Object Runway 09L/27R
Runway 09L/27R is a primary paved runway at Hannover Airport in Germany, used for commercial and passenger air traffic operations.
 E599162 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: Runway 09L/27R | Statement: [Hannover Airport, hasRunway, Runway 09L/27R]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Runway 09L/27R
Context triple: [Hannover Airport, hasRunway, Runway 09L/27R]
  • A. Runway 09L/27R
    Runway 09L/27R is a major east–west runway at Chicago O'Hare International Airport used for handling high volumes of commercial air traffic.
  • B. Runway 09L/27R
    Runway 09L/27R is one of London Heathrow Airport’s main east–west runways, used for a large share of its takeoffs and landings.
  • C. Runway 09L/27R
    Runway 09L/27R is one of the primary parallel runways used for commercial air traffic operations at São Paulo–Guarulhos International Airport in Brazil.
  • D. Runway 09L/27R
    Runway 09L/27R is one of the primary parallel runways used for commercial aircraft operations at Philadelphia International Airport.
  • E. Runway 09R/27L
    Runway 09R/27L is a major east–west runway at Chicago O'Hare International Airport used for handling high volumes of commercial air traffic.
  • 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: Runway 09L/27R
Triple: [Hannover Airport, hasRunway, Runway 09L/27R]
Generated description
Runway 09L/27R is a primary paved runway at Hannover Airport in Germany, used for commercial and passenger air traffic operations.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Runway 09L/27R
Target entity description: Runway 09L/27R is a primary paved runway at Hannover Airport in Germany, used for commercial and passenger air traffic operations.
  • A. Runway 09L/27R
    Runway 09L/27R is a major east–west runway at Chicago O'Hare International Airport used for handling high volumes of commercial air traffic.
  • B. Runway 09L/27R
    Runway 09L/27R is one of the primary parallel runways used for commercial aircraft operations at Philadelphia International Airport.
  • C. Runway 09L/27R
    Runway 09L/27R is one of London Heathrow Airport’s main east–west runways, used for a large share of its takeoffs and landings.
  • D. Runway 09L/27R
    Runway 09L/27R is one of the primary parallel runways used for commercial air traffic operations at São Paulo–Guarulhos International Airport in Brazil.
  • E. Runway 09R/27L
    Runway 09R/27L is a major east–west runway at Chicago O'Hare International Airport used for handling high volumes of commercial air traffic.
  • 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_69bd446a42c88190b7ecbef006561d55 completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd7bd4a9888190a79ef8e64c764f86 completed March 20, 2026, 4:54 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6cad46d4081908f685d961d100d42 completed March 27, 2026, 6:22 p.m.
NEDg Description generation batch_69c6cc960e088190bd9643aa1c46128d completed March 27, 2026, 6:29 p.m.
NED2 Entity disambiguation (via description) batch_69c6cd4d50948190ac60ec518f00e5d8 completed March 27, 2026, 6:32 p.m.
Created at: March 20, 2026, 1:51 p.m.