Triple

T9593794
Position Surface form Disambiguated ID Type / Status
Subject The Boat Service E231480 entity
Predicate cooperatesWith P435 FINISHED
Object SAS
SAS (Scandinavian Airlines) is the flag carrier of Denmark, Norway, and Sweden, providing international and domestic air travel across Europe, North America, and Asia.
E245449 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: SAS | Statement: [The Boat Service, cooperatesWith, SAS]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: SAS
Context triple: [The Boat Service, cooperatesWith, SAS]
  • A. SAS
    SAS is a widely used statistical software suite for advanced analytics, business intelligence, data management, and predictive modeling.
  • 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 the common abbreviation for the San Antonio Silver Stars, a former Women’s National Basketball Association (WNBA) team based in San Antonio, Texas.
  • D. SAS
    SAS is the station code for San Antonio railway station.
  • E. SAS
    SAS is the common abbreviation for the San Antonio Scorpions, a former professional soccer team based in San Antonio, Texas.
  • 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: SAS
Triple: [The Boat Service, cooperatesWith, SAS]
Generated description
SAS (Scandinavian Airlines) is the flag carrier of Denmark, Norway, and Sweden, providing international and domestic air travel across Europe, North America, and Asia.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: SAS
Target entity description: SAS (Scandinavian Airlines) is the flag carrier of Denmark, Norway, and Sweden, providing international and domestic air travel across Europe, North America, and Asia.
  • A. SAS chosen
    SAS is a major Scandinavian airline group that provides passenger and cargo air transport services primarily across Europe and to intercontinental destinations.
  • 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 the common abbreviation for the San Antonio Silver Stars, a former Women’s National Basketball Association (WNBA) team based in San Antonio, Texas.
  • E. SAS
    SAS is the School of Arts and Sciences at the University of Pennsylvania, encompassing the university’s core liberal arts and sciences departments and programs.
  • F. None of above.

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_69ca8482884481908eccdfdf64d6fbf7 completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd9a134b0c81908a568e5d2ecfbb92 completed April 1, 2026, 10:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69d161938e108190aea76d528f9208a2 completed April 4, 2026, 7:08 p.m.
NEDg Description generation batch_69d1624400b8819085b1c1a93cddc3f6 completed April 4, 2026, 7:11 p.m.
NED2 Entity disambiguation (via description) batch_69d162b39c888190ae71b05ee2e132a8 completed April 4, 2026, 7:12 p.m.
Created at: March 30, 2026, 8:07 p.m.