Triple

T13076733
Position Surface form Disambiguated ID Type / Status
Subject Luang Prabang International Airport E329594 entity
Predicate ICAOcode P419 FINISHED
Object VLLB
VLLB is the ICAO airport code for Luang Prabang International Airport in Laos, which serves the historic city of Luang Prabang.
E1020012 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: VLLB | Statement: [Luang Prabang International Airport, ICAOcode, VLLB]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: VLLB
Context triple: [Luang Prabang International Airport, ICAOcode, VLLB]
  • A. VLB
    VLB is a now-obsolete high-speed local computer bus standard developed by VESA in the early 1990s to improve graphics and system performance on 486-based PCs.
  • B. VLL
    VLL is the three-letter IATA airport code for Valladolid Airport in Spain.
  • C. LLD
    LLD is a doctoral-level law degree focused on advanced legal research and scholarship.
  • D. LLD
    LLD is the IATA airport code for Lydda Airport, the historical name for what is now Ben Gurion Airport near Tel Aviv, Israel.
  • E. LLD
    LLD is the LLVM project’s high-performance, modular linker designed as a drop-in replacement for traditional system linkers across multiple platforms.
  • 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: VLLB
Triple: [Luang Prabang International Airport, ICAOcode, VLLB]
Generated description
VLLB is the ICAO airport code for Luang Prabang International Airport in Laos, which serves the historic city of Luang Prabang.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: VLLB
Target entity description: VLLB is the ICAO airport code for Luang Prabang International Airport in Laos, which serves the historic city of Luang Prabang.
  • A. VLB
    VLB is a now-obsolete high-speed local computer bus standard developed by VESA in the early 1990s to improve graphics and system performance on 486-based PCs.
  • B. VLL
    VLL is the three-letter IATA airport code for Valladolid Airport in Spain.
  • C. LLD
    LLD is a doctoral-level law degree focused on advanced legal research and scholarship.
  • D. LLD
    LLD is the IATA airport code for Lydda Airport, the historical name for what is now Ben Gurion Airport near Tel Aviv, Israel.
  • E. LLD
    LLD is the LLVM project’s high-performance, modular linker designed as a drop-in replacement for traditional system linkers across multiple platforms.
  • 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_69d80771749c81909a6d9197b9504872 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69d98117209081908272021013df2222 completed April 10, 2026, 11 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6d60aaac48190b5b724a19cad5279 completed May 3, 2026, 4:58 a.m.
NEDg Description generation batch_69f6da9ed7bc8190b1a451ea2ada811d completed May 3, 2026, 5:18 a.m.
NED2 Entity disambiguation (via description) batch_69f6db6950b08190a868c9371ff0a34e completed May 3, 2026, 5:21 a.m.
Created at: April 9, 2026, 9:01 p.m.