Triple

T14872881
Position Surface form Disambiguated ID Type / Status
Subject Smara E349793 entity
Predicate airportIATAcode P418 FINISHED
Object SMW
SMW is the IATA airport code for Smara Airport, serving the town of Smara in Western Sahara.
 E1124283 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: SMW | Statement: [Smara, airportIATAcode, SMW]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: SMW
Context triple: [Smara, airportIATAcode, SMW]
  • A. SWM
    SWM is the municipal utility company of Munich, Germany, responsible for providing services such as energy, water, and public transportation.
  • B. SWC
    SWC is the acronym for the South Western Command of the Indian Army, a major operational command responsible for defense and military operations in India’s western sector.
  • C. SWC
    SWC is the abbreviation for the Southwest Conference, a former NCAA Division I college athletic conference that primarily featured schools from Texas and the surrounding region.
  • D. SMWK
    SMWK is the abbreviation for the Saxon State Ministry responsible for science, culture, and tourism in the German state of Saxony.
  • E. SWMP
    SWMP (System-Wide Monitoring Program) is a long-term environmental monitoring initiative that tracks water quality, weather, and ecological conditions across the National Estuarine Research Reserve System.
  • 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: SMW
Triple: [Smara, airportIATAcode, SMW]
Generated description
SMW is the IATA airport code for Smara Airport, serving the town of Smara in Western Sahara.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: SMW
Target entity description: SMW is the IATA airport code for Smara Airport, serving the town of Smara in Western Sahara.
  • A. SWM
    SWM is the municipal utility company of Munich, Germany, responsible for providing services such as energy, water, and public transportation.
  • B. SWC
    SWC is the acronym for the South Western Command of the Indian Army, a major operational command responsible for defense and military operations in India’s western sector.
  • C. SWC
    SWC is the abbreviation for the Southwest Conference, a former NCAA Division I college athletic conference that primarily featured schools from Texas and the surrounding region.
  • D. SMWK
    SMWK is the abbreviation for the Saxon State Ministry responsible for science, culture, and tourism in the German state of Saxony.
  • E. SWMP
    SWMP (System-Wide Monitoring Program) is a long-term environmental monitoring initiative that tracks water quality, weather, and ecological conditions across the National Estuarine Research Reserve System.
  • 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_69d822ee4f408190b6ac3b2fa434f0df completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69ded5e2c94c8190a16f05ea81701fc1 completed April 15, 2026, 12:03 a.m.
NED1 Entity disambiguation (via context triple) batch_69fe65129a588190bbad294b500f411f completed May 8, 2026, 10:34 p.m.
NEDg Description generation batch_69fe66a5f3a88190827c6c9247323153 completed May 8, 2026, 10:41 p.m.
NED2 Entity disambiguation (via description) batch_69fe6736ff34819098524e4401a414aa completed May 8, 2026, 10:44 p.m.
Created at: April 10, 2026, 1:55 a.m.