Triple

T1458363
Position Surface form Disambiguated ID Type / Status
Subject Saudia E31450 entity
Predicate ICAOcode P419 FINISHED
Object SVA
SVA is the ICAO airline designator used to identify Saudia, the flag carrier airline of Saudi Arabia, in international aviation operations.
 E168122 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: SVA | Statement: [Saudia, ICAOcode, SVA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: SVA
Context triple: [Saudia, ICAOcode, SVA]
  • A. SVC
    SVC is scikit-learn’s implementation of a Support Vector Machine classifier used for supervised learning tasks such as binary and multiclass classification.
  • B. SAS
    SAS is a widely used statistical software suite for advanced analytics, business intelligence, data management, and predictive modeling.
  • C. SAS
    SAS is a high-speed, point-to-point serial interface standard commonly used to connect enterprise storage devices like hard drives and solid-state drives to servers.
  • D. SAS
    SAS is an elite special forces unit of the British Army renowned for its covert operations, counterterrorism expertise, and rigorous selection process.
  • E. SAS
    SAS is the standard abbreviation used for the NBA team San Antonio Spurs.
  • 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: SVA
Triple: [Saudia, ICAOcode, SVA]
Generated description
SVA is the ICAO airline designator used to identify Saudia, the flag carrier airline of Saudi Arabia, in international aviation operations.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: SVA
Target entity description: SVA is the ICAO airline designator used to identify Saudia, the flag carrier airline of Saudi Arabia, in international aviation operations.
  • A. SVC
    SVC is scikit-learn’s implementation of a Support Vector Machine classifier used for supervised learning tasks such as binary and multiclass classification.
  • B. SAS
    SAS is an elite special forces unit of the British Army renowned for its covert operations, counterterrorism expertise, and rigorous selection process.
  • C. SAS
    SAS is a widely used statistical software suite for advanced analytics, business intelligence, data management, and predictive modeling.
  • D. SAS
    SAS is a high-speed, point-to-point serial interface standard commonly used to connect enterprise storage devices like hard drives and solid-state drives to servers.
  • E. SAS
    SAS is the standard abbreviation used for the NBA team San Antonio Spurs.
  • 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_69a49917dfc081909acdbdf5d684f1ef completed March 1, 2026, 7:52 p.m.
NER Named-entity recognition batch_69a4c59a462881908e84b27846a6bc04 completed March 1, 2026, 11:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad0e7643e081909a088035faf2022d completed March 8, 2026, 5:51 a.m.
NEDg Description generation batch_69ad121fee9c81909efddee10191b791 completed March 8, 2026, 6:07 a.m.
NED2 Entity disambiguation (via description) batch_69ad127f25548190bdbcf99132237ad4 completed March 8, 2026, 6:09 a.m.
Created at: March 1, 2026, 8 p.m.