Triple

T1550672
Position Surface form Disambiguated ID Type / Status
Subject New Springville E33081 entity
Predicate servedByBusRoute P14525 FINISHED
Object SIM31
SIM31 is an express bus route in New York City that provides commuter service between Staten Island and Manhattan.
 E175829 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: SIM31 | Statement: [New Springville, servedByBusRoute, SIM31]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: SIM31
Context triple: [New Springville, servedByBusRoute, SIM31]
  • A. SIM
    SIM is the commonly used abbreviation for the Science and Industry Museum in Manchester, a major UK museum dedicated to the history and impact of science, technology, and industry.
  • B. eSIM
    eSIM is an embedded, programmable SIM technology built into devices that lets users activate and switch mobile carriers digitally without needing a physical SIM card.
  • C. SMF
    SMF is the three-letter IATA airport code for Sacramento International Airport, the primary commercial airport serving California’s capital city.
  • D. SMDS
    SMDS is the abbreviated name for the U.S. Army Space and Missile Defense School, a training institution focused on space and missile defense operations.
  • E. Fitel
    Fitel was a financial technology startup where Jeff Bezos worked early in his career, before joining D. E. Shaw and later founding Amazon.
  • 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: SIM31
Triple: [New Springville, servedByBusRoute, SIM31]
Generated description
SIM31 is an express bus route in New York City that provides commuter service between Staten Island and Manhattan.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: SIM31
Target entity description: SIM31 is an express bus route in New York City that provides commuter service between Staten Island and Manhattan.
  • A. SIM
    SIM is the commonly used abbreviation for the Science and Industry Museum in Manchester, a major UK museum dedicated to the history and impact of science, technology, and industry.
  • B. eSIM
    eSIM is an embedded, programmable SIM technology built into devices that lets users activate and switch mobile carriers digitally without needing a physical SIM card.
  • C. SMF
    SMF is the three-letter IATA airport code for Sacramento International Airport, the primary commercial airport serving California’s capital city.
  • D. SMDS
    SMDS is the abbreviated name for the U.S. Army Space and Missile Defense School, a training institution focused on space and missile defense operations.
  • E. Fitel
    Fitel was a financial technology startup where Jeff Bezos worked early in his career, before joining D. E. Shaw and later founding Amazon.
  • 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_69a885ee6db8819099502bc5ce8af881 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69aa61ddc9908190a4afca1c24400817 completed March 6, 2026, 5:10 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad30a29ae88190ab1b2ca97b8ed09c completed March 8, 2026, 8:17 a.m.
NEDg Description generation batch_69ad3196e92481909bd09e6c765a9698 completed March 8, 2026, 8:21 a.m.
NED2 Entity disambiguation (via description) batch_69ad32391ed881909826a80a90f18cb4 completed March 8, 2026, 8:24 a.m.
Created at: March 4, 2026, 7:26 p.m.