Triple

T7972681
Position Surface form Disambiguated ID Type / Status
Subject San Antonio station E185364 entity
Predicate code P1537 FINISHED
Object SAS
SAS is the station code for San Antonio railway station.
 E702595 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: [San Antonio station, code, SAS]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: SAS
Context triple: [San Antonio station, code, SAS]
  • A. 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.
  • 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: SAS
Triple: [San Antonio station, code, SAS]
Generated description
SAS is the station code for San Antonio railway station.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: SAS
Target entity description: SAS is the station code for San Antonio railway station.
  • A. SAS
    SAS is the standard abbreviation used for the NBA team San Antonio Spurs.
  • B. 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.
  • 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 a widely used statistical software suite for advanced analytics, business intelligence, data management, and predictive modeling.
  • E. SAS
    SAS is a major Scandinavian airline group that provides passenger and cargo air transport services primarily across Europe and to intercontinental destinations.
  • 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_69ca8297699481909b75a405f01e03af completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb3bd580dc819084be5b7963b6029c completed March 31, 2026, 3:13 a.m.
NED1 Entity disambiguation (via context triple) batch_69cbe0b207ec8190a1a78e77a6bdb15e completed March 31, 2026, 2:56 p.m.
NEDg Description generation batch_69cbe43c4d2081909a8f5763252d88f1 completed March 31, 2026, 3:11 p.m.
NED2 Entity disambiguation (via description) batch_69cc193e73cc819085797ef363a37079 completed March 31, 2026, 6:58 p.m.
Created at: March 30, 2026, 5:13 p.m.