Triple

T13909433
Position Surface form Disambiguated ID Type / Status
Subject Belle Harbor E334444 entity
Predicate servedByExpressBusRoute P39381 FINISHED
Object MTA QM17
MTA QM17 is a New York City express bus route that provides commuter service between Belle Harbor in Queens and Midtown Manhattan.
E1070251 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: MTA QM17 | Statement: [Belle Harbor, servedByExpressBusRoute, MTA QM17]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: MTA QM17
Context triple: [Belle Harbor, servedByExpressBusRoute, MTA QM17]
  • A. MTA
    MTA is the public transportation authority serving the New York City metropolitan area, operating subways, buses, and commuter rail systems.
  • B. MTA
    MTA is the commonly used abbreviation for the Maryland Transit Administration, the state agency that operates public transportation services in and around Baltimore, Maryland.
  • C. MTA
    MTA is the abbreviated name historically used for Boston’s Metropolitan Transit Authority, the predecessor to today’s MBTA public transit system.
  • D. MTA
    MTA is the main regulated equities market segment of Borsa Italiana, where shares of medium and large Italian and international companies are listed and traded.
  • E. MTA
    MTA is an abbreviation for the Project on Managing the Atom, a research initiative focused on nuclear policy, security, 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: MTA QM17
Triple: [Belle Harbor, servedByExpressBusRoute, MTA QM17]
Generated description
MTA QM17 is a New York City express bus route that provides commuter service between Belle Harbor in Queens and Midtown Manhattan.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: MTA QM17
Target entity description: MTA QM17 is a New York City express bus route that provides commuter service between Belle Harbor in Queens and Midtown Manhattan.
  • A. MTA
    MTA is the public transportation authority serving the New York City metropolitan area, operating subways, buses, and commuter rail systems.
  • B. MTA
    MTA is the commonly used abbreviation for the Maryland Transit Administration, the state agency that operates public transportation services in and around Baltimore, Maryland.
  • C. MTA
    MTA is the abbreviated name historically used for Boston’s Metropolitan Transit Authority, the predecessor to today’s MBTA public transit system.
  • D. MTA
    MTA is the Hungarian Academy of Sciences, Hungary’s foremost scholarly institution overseeing and supporting scientific research across disciplines.
  • E. MTA
    MTA is an abbreviation for the Project on Managing the Atom, a research initiative focused on nuclear policy, security, 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_69d81c5eaa9c819083b1ff8689179565 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de2721ec6c8190888f4a9d004eb8e0 completed April 14, 2026, 11:38 a.m.
NED1 Entity disambiguation (via context triple) batch_69f7ce7638a88190aae1b59c00ee27ce completed May 3, 2026, 10:38 p.m.
NEDg Description generation batch_69f9fd56da288190b2bd33bc496c3fb9 completed May 5, 2026, 2:23 p.m.
NED2 Entity disambiguation (via description) batch_69fb039fdb1c8190ad5286d1cfe80a29 completed May 6, 2026, 9:02 a.m.
Created at: April 9, 2026, 10:16 p.m.