Triple

T10567017
Position Surface form Disambiguated ID Type / Status
Subject Olaya Herrera Airport E249376 entity
Predicate IATAcode P418 FINISHED
Object EOH
EOH is the IATA airport code for Olaya Herrera Airport, a domestic airport serving Medellín, Colombia.
 E872902 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: EOH | Statement: [Olaya Herrera Airport, IATAcode, EOH]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: EOH
Context triple: [Olaya Herrera Airport, IATAcode, EOH]
  • A. OEO
    OEO is the acronym for the U.S. federal Office of Economic Opportunity, a 1960s-era agency created to administer anti-poverty programs under President Lyndon B. Johnson’s War on Poverty.
  • B. EOHHS
    EOHHS is the Massachusetts state agency responsible for overseeing health and human services programs, including public health, Medicaid, and social services.
  • C. OHR
    OHR is the international body overseeing the civilian implementation of the Dayton Peace Agreement in Bosnia and Herzegovina.
  • D. OHE
    OHE is the Office of Health Equity, a governmental body focused on promoting fair and just access to health services and outcomes across all populations.
  • E. ÓE
    ÓE is the official abbreviation for Óbuda University, a higher education institution in Budapest, Hungary known for its engineering and technical programs.
  • 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: EOH
Triple: [Olaya Herrera Airport, IATAcode, EOH]
Generated description
EOH is the IATA airport code for Olaya Herrera Airport, a domestic airport serving Medellín, Colombia.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: EOH
Target entity description: EOH is the IATA airport code for Olaya Herrera Airport, a domestic airport serving Medellín, Colombia.
  • A. OEO
    OEO is the acronym for the U.S. federal Office of Economic Opportunity, a 1960s-era agency created to administer anti-poverty programs under President Lyndon B. Johnson’s War on Poverty.
  • B. EOHHS
    EOHHS is the Massachusetts state agency responsible for overseeing health and human services programs, including public health, Medicaid, and social services.
  • C. OHR
    OHR is the international body overseeing the civilian implementation of the Dayton Peace Agreement in Bosnia and Herzegovina.
  • D. OHE
    OHE is the Office of Health Equity, a governmental body focused on promoting fair and just access to health services and outcomes across all populations.
  • E. ÓE
    ÓE is the official abbreviation for Óbuda University, a higher education institution in Budapest, Hungary known for its engineering and technical programs.
  • 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_69d381c8bd708190acf3d275c908251e completed April 6, 2026, 9:50 a.m.
NER Named-entity recognition batch_69d5272ef5848190b76d671ea2d26314 completed April 7, 2026, 3:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69d94b42879481909f9c98b2579c10a1 completed April 10, 2026, 7:10 p.m.
NEDg Description generation batch_69d94d67e16481908efb939a3e65004c completed April 10, 2026, 7:20 p.m.
NED2 Entity disambiguation (via description) batch_69d95227a1f48190ab847606a9ae0500 completed April 10, 2026, 7:40 p.m.
Created at: April 6, 2026, 12:36 p.m.