Triple

T8722406
Position Surface form Disambiguated ID Type / Status
Subject Shore Acres, Staten Island E207042 entity
Predicate servedByExpressBus P6301 FINISHED
Object SIM30
SIM30 is a New York City express bus route that provides commuter service between Staten Island and Manhattan.
 E752878 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: SIM30 | Statement: [Shore Acres, Staten Island, servedByExpressBus, SIM30]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: SIM30
Context triple: [Shore Acres, Staten Island, servedByExpressBus, SIM30]
  • A. SIM31
    SIM31 is an express bus route in New York City that provides commuter service between Staten Island and Manhattan.
  • B. SIM4C
    SIM4C is an express bus route in New York City that provides commuter service between Staten Island and Manhattan.
  • C. SIM
    SIM (Subscriber Identity Module) is a secure smart card or embedded chip used in mobile devices to store subscriber credentials and enable authentication and access to cellular networks.
  • D. SIM
    SIM is the vehicle registration code used on license plates for vehicles registered in the Simmern region of Germany.
  • E. 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.
  • 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: SIM30
Triple: [Shore Acres, Staten Island, servedByExpressBus, SIM30]
Generated description
SIM30 is a New York City express bus route that provides commuter service between Staten Island and Manhattan.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: SIM30
Target entity description: SIM30 is a New York City express bus route that provides commuter service between Staten Island and Manhattan.
  • A. SIM31
    SIM31 is an express bus route in New York City that provides commuter service between Staten Island and Manhattan.
  • B. SIM4C
    SIM4C is an express bus route in New York City that provides commuter service between Staten Island and Manhattan.
  • C. SIM
    SIM (Subscriber Identity Module) is a secure smart card or embedded chip used in mobile devices to store subscriber credentials and enable authentication and access to cellular networks.
  • D. SIM
    SIM is the vehicle registration code used on license plates for vehicles registered in the Simmern region of Germany.
  • E. 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.
  • 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_69ca835811d8819081ea00fd2a2c9a1c completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc5d0609f48190adc56226724b16c6 completed March 31, 2026, 11:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69cf290001108190a90784b13a0a25b1 completed April 3, 2026, 2:42 a.m.
NEDg Description generation batch_69cf2bd32cc881909ac8a61befa9929e completed April 3, 2026, 2:54 a.m.
NED2 Entity disambiguation (via description) batch_69cf2c69f83481909423858668d03a8b completed April 3, 2026, 2:56 a.m.
Created at: March 30, 2026, 6:36 p.m.