Triple

T13001459
Position Surface form Disambiguated ID Type / Status
Subject Project on Managing the Atom E322178 entity
Predicate abbreviation P43 FINISHED
Object MTA
MTA is an abbreviation for the Project on Managing the Atom, a research initiative focused on nuclear policy, security, and governance.
 E1016607 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 | Statement: [Project on Managing the Atom, abbreviation, MTA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: MTA
Context triple: [Project on Managing the Atom, abbreviation, MTA]
  • A. 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.
  • B. MTA
    MTA is the abbreviated name historically used for Boston’s Metropolitan Transit Authority, the predecessor to today’s MBTA public transit system.
  • C. MTA
    MTA is the public transportation authority serving the New York City metropolitan area, operating subways, buses, and commuter rail systems.
  • 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 the main regulated equities market segment of Borsa Italiana, where shares of medium and large Italian and international companies are listed and traded.
  • 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
Triple: [Project on Managing the Atom, abbreviation, MTA]
Generated description
MTA is an abbreviation for the Project on Managing the Atom, a research initiative focused on nuclear policy, security, and governance.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: MTA
Target entity description: MTA is an abbreviation for the Project on Managing the Atom, a research initiative focused on nuclear policy, security, and governance.
  • A. 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.
  • B. MTA
    MTA is the abbreviated name historically used for Boston’s Metropolitan Transit Authority, the predecessor to today’s MBTA public transit system.
  • C. 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.
  • D. MTA
    MTA is the public transportation authority serving the New York City metropolitan area, operating subways, buses, and commuter rail systems.
  • E. MTA
    MTA is the Hungarian Academy of Sciences, Hungary’s foremost scholarly institution overseeing and supporting scientific research across disciplines.
  • 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_69d807657e8c8190bd9435ee2f823845 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69d97e9828748190b2ad9ea29180b7d3 completed April 10, 2026, 10:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6c103e49c8190a140527f24b5c799 completed May 3, 2026, 3:29 a.m.
NEDg Description generation batch_69f6c562d10c8190b76dbf50a0101bae completed May 3, 2026, 3:47 a.m.
NED2 Entity disambiguation (via description) batch_69f6c635fc888190891a79da9d7984a0 completed May 3, 2026, 3:51 a.m.
Created at: April 9, 2026, 8:47 p.m.