Triple

T14607617
Position Surface form Disambiguated ID Type / Status
Subject Sulaimaniyah International Airport E342872 entity
Predicate ICAOCode P419 FINISHED
Object ORSU
ORSU is the ICAO airport code assigned to Sulaimaniyah International Airport in the Kurdistan Region of Iraq.
E1108333 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: ORSU | Statement: [Sulaimaniyah International Airport, ICAOCode, ORSU]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: ORSU
Context triple: [Sulaimaniyah International Airport, ICAOCode, ORSU]
  • A. Ors
    Ors is a small commune in northern France, known for its World War I history and military cemetery.
  • B. ORU
    ORU is the IATA airport code for Juan Mendoza Airport, a regional airport serving the city of Oruro in Bolivia.
  • C. ORU
    ORU is a private Christian liberal arts university in Tulsa, Oklahoma, founded by evangelist Oral Roberts and known for integrating faith-based education with a diverse range of academic programs.
  • D. URS
    URS was the FIFA country code used to represent the Soviet Union national football team in international competitions.
  • E. Oroshori
    Oroshori is an Eastern Iranian Pamiri language spoken in parts of Tajikistan and Afghanistan, closely related to Shughni and sharing many linguistic features with it.
  • 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: ORSU
Triple: [Sulaimaniyah International Airport, ICAOCode, ORSU]
Generated description
ORSU is the ICAO airport code assigned to Sulaimaniyah International Airport in the Kurdistan Region of Iraq.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: ORSU
Target entity description: ORSU is the ICAO airport code assigned to Sulaimaniyah International Airport in the Kurdistan Region of Iraq.
  • A. Ors
    Ors is a small commune in northern France, known for its World War I history and military cemetery.
  • B. ORU
    ORU is the IATA airport code for Juan Mendoza Airport, a regional airport serving the city of Oruro in Bolivia.
  • C. ORU
    ORU is a private Christian liberal arts university in Tulsa, Oklahoma, founded by evangelist Oral Roberts and known for integrating faith-based education with a diverse range of academic programs.
  • D. URS
    URS was the FIFA country code used to represent the Soviet Union national football team in international competitions.
  • E. Oroshori
    Oroshori is an Eastern Iranian Pamiri language spoken in parts of Tajikistan and Afghanistan, closely related to Shughni and sharing many linguistic features with it.
  • 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_69d822dec68081908c2553145c4051dc completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb44d327c8190a8d20568429d0f80 completed April 14, 2026, 9:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd94d09e988190a2a2a1332397b412 completed May 8, 2026, 7:46 a.m.
NEDg Description generation batch_69fd9828129c8190bd7445e99dadc618 completed May 8, 2026, 8 a.m.
NED2 Entity disambiguation (via description) batch_69fd98cf0bcc81909dac826a32daaf04 completed May 8, 2026, 8:03 a.m.
Created at: April 10, 2026, 1:25 a.m.