Triple

T9534081
Position Surface form Disambiguated ID Type / Status
Subject Riverdale E229967 entity
Predicate servedByBus P14525 FINISHED
Object BxM2
BxM2 is an express bus route in New York City that provides commuter service between the Bronx and Manhattan.
 E807228 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: BxM2 | Statement: [Riverdale, servedByBus, BxM2]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: BxM2
Context triple: [Riverdale, servedByBus, BxM2]
  • A. BxM1
    BxM1 is an express bus route in New York City that provides commuter service between the Bronx and Manhattan.
  • B. BXM
    BXM is the railway station code for Brussels-South (Bruxelles-Midi / Brussel-Zuid), the main international and domestic rail hub in Brussels, Belgium.
  • C. Bx10
    The Bx10 is a New York City bus route in the Bronx that connects the Riverdale neighborhood with other parts of the borough.
  • D. BxM18
    BxM18 is an express bus route in New York City that connects the Riverdale neighborhood in the Bronx with Manhattan.
  • E. BMM
    BMM (Business Motivation Model) is a standardized framework by the Object Management Group for modeling and analyzing an organization’s business plans, motivations, and governance.
  • 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: BxM2
Triple: [Riverdale, servedByBus, BxM2]
Generated description
BxM2 is an express bus route in New York City that provides commuter service between the Bronx and Manhattan.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: BxM2
Target entity description: BxM2 is an express bus route in New York City that provides commuter service between the Bronx and Manhattan.
  • A. BxM1
    BxM1 is an express bus route in New York City that provides commuter service between the Bronx and Manhattan.
  • B. BXM
    BXM is the railway station code for Brussels-South (Bruxelles-Midi / Brussel-Zuid), the main international and domestic rail hub in Brussels, Belgium.
  • C. Bx10
    The Bx10 is a New York City bus route in the Bronx that connects the Riverdale neighborhood with other parts of the borough.
  • D. BxM18
    BxM18 is an express bus route in New York City that connects the Riverdale neighborhood in the Bronx with Manhattan.
  • E. BMM
    BMM (Business Motivation Model) is a standardized framework by the Object Management Group for modeling and analyzing an organization’s business plans, motivations, and governance.
  • 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_69ca8479934c81908006d0e6e970ae05 completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd98c9fef88190beb291b41ee26066 completed April 1, 2026, 10:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69d15275e4c08190a8aeb02caff052d8 completed April 4, 2026, 6:03 p.m.
NEDg Description generation batch_69d1566bfaa08190afa29757b20539cf completed April 4, 2026, 6:20 p.m.
NED2 Entity disambiguation (via description) batch_69d156bc99f48190a9371ab2e442bca4 completed April 4, 2026, 6:21 p.m.
Created at: March 30, 2026, 8 p.m.