Triple

T8197118
Position Surface form Disambiguated ID Type / Status
Subject Salinas Municipal Airport E191460 entity
Predicate IATAcode P418 FINISHED
Object SNS
SNS is the three-letter IATA airport code assigned to Salinas Municipal Airport in Salinas, California.
 E718496 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: SNS | Statement: [Salinas Municipal Airport, IATAcode, SNS]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: SNS
Context triple: [Salinas Municipal Airport, IATAcode, SNS]
  • A. SNS
    SNS is the School of Natural Sciences at the University of California, Merced, which focuses on education and research in scientific disciplines such as biology, chemistry, physics, and related fields.
  • B. SNS
    SNS is the National Rail station code for Staines railway station in Surrey, England.
  • C. SNS
    SNS is the acronym for the Scuola Normale Superiore di Pisa, an elite Italian higher education and research institution renowned for its rigorous academic standards.
  • D. SNA
    SNA is the IATA airport code for John Wayne Airport, a commercial and general aviation airport serving Orange County, California.
  • E. SNA
    SNA is the commonly used abbreviation for the United Nations System of National Accounts, the international standard framework for measuring a country’s economic activity.
  • 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: SNS
Triple: [Salinas Municipal Airport, IATAcode, SNS]
Generated description
SNS is the three-letter IATA airport code assigned to Salinas Municipal Airport in Salinas, California.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: SNS
Target entity description: SNS is the three-letter IATA airport code assigned to Salinas Municipal Airport in Salinas, California.
  • A. SNS
    SNS is the National Rail station code for Staines railway station in Surrey, England.
  • B. SNS
    SNS is the School of Natural Sciences at the University of California, Merced, which focuses on education and research in scientific disciplines such as biology, chemistry, physics, and related fields.
  • C. SNS
    SNS is the acronym for the Scuola Normale Superiore di Pisa, an elite Italian higher education and research institution renowned for its rigorous academic standards.
  • D. SNA
    SNA is the IATA airport code for John Wayne Airport, a commercial and general aviation airport serving Orange County, California.
  • E. SNA
    SNA is the commonly used abbreviation for the United Nations System of National Accounts, the international standard framework for measuring a country’s economic activity.
  • 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_69ca82c6e9548190a4c5ca14516e4417 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb5c2341f881908be59c378896e5bc completed March 31, 2026, 5:31 a.m.
NED1 Entity disambiguation (via context triple) batch_69ccedb3cd488190b87e134dd0426a6d completed April 1, 2026, 10:04 a.m.
NEDg Description generation batch_69ccf1b706f08190993f4a75eac5f49c completed April 1, 2026, 10:21 a.m.
NED2 Entity disambiguation (via description) batch_69cd05ac594c819087d23a7318fd7704 completed April 1, 2026, 11:46 a.m.
Created at: March 30, 2026, 5:42 p.m.