Triple

T13158887
Position Surface form Disambiguated ID Type / Status
Subject Leros Municipal Airport E312668 entity
Predicate IATAcode P418 FINISHED
Object LRS
LRS is the IATA airport code for Leros Municipal Airport, a small regional airport serving the Greek island of Leros in the Dodecanese.
E1024391 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: LRS | Statement: [Leros Municipal Airport, IATAcode, LRS]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: LRS
Context triple: [Leros Municipal Airport, IATAcode, LRS]
  • A. LSR
    LSR is a prestigious women’s college in New Delhi, India, renowned for its academic excellence and affiliation with the University of Delhi.
  • B. LRD
    LRD is the official currency code for the Liberian dollar, the legal tender used in Liberia.
  • C. LRPS
    LRPS is a distinction awarded by the Royal Photographic Society to photographers who demonstrate a high standard of technical competence and creative ability.
  • D. DRS
    DRS is the stock ticker symbol for Leonardo DRS, an American defense technology company specializing in advanced military and intelligence systems.
  • E. DRS
    DRS is the three-letter IATA airport code for Dresden Airport in Dresden, Germany.
  • 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: LRS
Triple: [Leros Municipal Airport, IATAcode, LRS]
Generated description
LRS is the IATA airport code for Leros Municipal Airport, a small regional airport serving the Greek island of Leros in the Dodecanese.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: LRS
Target entity description: LRS is the IATA airport code for Leros Municipal Airport, a small regional airport serving the Greek island of Leros in the Dodecanese.
  • A. LSR
    LSR is a prestigious women’s college in New Delhi, India, renowned for its academic excellence and affiliation with the University of Delhi.
  • B. LRD
    LRD is the official currency code for the Liberian dollar, the legal tender used in Liberia.
  • C. LRPS
    LRPS is a distinction awarded by the Royal Photographic Society to photographers who demonstrate a high standard of technical competence and creative ability.
  • D. DRS
    DRS is the stock ticker symbol for Leonardo DRS, an American defense technology company specializing in advanced military and intelligence systems.
  • E. DRS
    DRS is the three-letter IATA airport code for Dresden Airport in Dresden, Germany.
  • 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_69d806ac3ee081909b2fd27d060aa974 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d98c0971008190869e9de710f4c579 completed April 10, 2026, 11:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6eaf2ae688190b3484989791977ce completed May 3, 2026, 6:28 a.m.
NEDg Description generation batch_69f6ebec15188190a8a07af6eb447edf completed May 3, 2026, 6:32 a.m.
NED2 Entity disambiguation (via description) batch_69f6ec7fe56481909e1ed69df593fa34 completed May 3, 2026, 6:34 a.m.
Created at: April 9, 2026, 9:12 p.m.