Triple

T4483957
Position Surface form Disambiguated ID Type / Status
Subject Oran Ahmed Ben Bella Airport E107190 entity
Predicate IATAcode P418 FINISHED
Object ORN
ORN is the IATA airport code for Oran Ahmed Ben Bella Airport, the main international airport serving Oran in northwestern Algeria.
 E446650 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: ORN | Statement: [Oran Ahmed Ben Bella Airport, IATAcode, ORN]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: ORN
Context triple: [Oran Ahmed Ben Bella Airport, IATAcode, ORN]
  • A. OR
    OR is the official two-letter United States Postal Service abbreviation for the state of Oregon.
  • B. ORS
    ORS is the commonly used abbreviation for the Oregon Revised Statutes, the codified laws governing the U.S. state of Oregon.
  • C. ONS
    ONS is the United Kingdom’s largest independent producer of official statistics and its recognized national statistical institute.
  • D. ORY
    ORY is the three-letter IATA airport code for Paris Orly Airport, a major international airport serving the Paris metropolitan area in France.
  • E. ORIA
    ORIA is a division of the U.S. Environmental Protection Agency responsible for developing and implementing programs and regulations to protect the public from radiation and indoor air pollution.
  • 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: ORN
Triple: [Oran Ahmed Ben Bella Airport, IATAcode, ORN]
Generated description
ORN is the IATA airport code for Oran Ahmed Ben Bella Airport, the main international airport serving Oran in northwestern Algeria.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: ORN
Target entity description: ORN is the IATA airport code for Oran Ahmed Ben Bella Airport, the main international airport serving Oran in northwestern Algeria.
  • A. OR
    OR is the official two-letter United States Postal Service abbreviation for the state of Oregon.
  • B. ORS
    ORS is the commonly used abbreviation for the Oregon Revised Statutes, the codified laws governing the U.S. state of Oregon.
  • C. ONS
    ONS is the United Kingdom’s largest independent producer of official statistics and its recognized national statistical institute.
  • D. ORY
    ORY is the three-letter IATA airport code for Paris Orly Airport, a major international airport serving the Paris metropolitan area in France.
  • E. ORIA
    ORIA is a division of the U.S. Environmental Protection Agency responsible for developing and implementing programs and regulations to protect the public from radiation and indoor air pollution.
  • 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_69bd43f84f788190a1383579c4a595be completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd52a54c6c8190a7421bea6e3c00f1 completed March 20, 2026, 1:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69bd679792f48190a19ce4ab91cab3bc completed March 20, 2026, 3:28 p.m.
NEDg Description generation batch_69bd6a1e07208190aab48ee3e7b7728a completed March 20, 2026, 3:39 p.m.
NED2 Entity disambiguation (via description) batch_69bd6a8d928c8190b2208431df458863 completed March 20, 2026, 3:41 p.m.
Created at: March 20, 2026, 12:58 p.m.