Triple

T3562105
Position Surface form Disambiguated ID Type / Status
Subject Valladolid Airport E75361 entity
Predicate IATAcode P418 FINISHED
Object VLL
VLL is the three-letter IATA airport code for Valladolid Airport in Spain.
 E369130 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: VLL | Statement: [Valladolid Airport, IATAcode, VLL]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: VLL
Context triple: [Valladolid Airport, IATAcode, VLL]
  • A. VL
    VL is the vehicle registration code used on license plates for vehicles registered in Râmnicu Vâlcea, Romania.
  • B. VLG
    VLG is the ICAO airline designator used to identify Vueling, a Spanish low-cost carrier based in Barcelona.
  • C. VELO
    VELO is the high-precision vertex detector of the LHCb experiment at CERN, designed to measure particle trajectories very close to the proton–proton collision point.
  • D. V.
    V. is Thomas Pynchon's 1963 debut novel, a complex, postmodern work that interweaves multiple narratives and historical periods in a quest surrounding the mysterious figure or concept known only as "V."
  • E. VIR
    VIR is the ICAO airline designator used to identify Virgin Atlantic in international aviation operations.
  • 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: VLL
Triple: [Valladolid Airport, IATAcode, VLL]
Generated description
VLL is the three-letter IATA airport code for Valladolid Airport in Spain.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: VLL
Target entity description: VLL is the three-letter IATA airport code for Valladolid Airport in Spain.
  • A. VL
    VL is the vehicle registration code used on license plates for vehicles registered in Râmnicu Vâlcea, Romania.
  • B. VLG
    VLG is the ICAO airline designator used to identify Vueling, a Spanish low-cost carrier based in Barcelona.
  • C. VELO
    VELO is the high-precision vertex detector of the LHCb experiment at CERN, designed to measure particle trajectories very close to the proton–proton collision point.
  • D. V.
    V. is Thomas Pynchon's 1963 debut novel, a complex, postmodern work that interweaves multiple narratives and historical periods in a quest surrounding the mysterious figure or concept known only as "V."
  • E. VIR
    VIR is the ICAO airline designator used to identify Virgin Atlantic in international aviation operations.
  • 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_69ad85d45090819086f34fb85d850a1e completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc08bdde88190915d2f6ddf26e00e completed March 8, 2026, 6:31 p.m.
NED1 Entity disambiguation (via context triple) batch_69b3bba21960819094676de7c4740fd9 completed March 13, 2026, 7:24 a.m.
NEDg Description generation batch_69b3bf69741481909e3d5ed71bb0e026 completed March 13, 2026, 7:40 a.m.
NED2 Entity disambiguation (via description) batch_69b3f299cfd08190948e602e8efab213 completed March 13, 2026, 11:18 a.m.
Created at: March 8, 2026, 3:21 p.m.