Triple

T5599243
Position Surface form Disambiguated ID Type / Status
Subject Maryland Transit Administration E147074 entity
Predicate abbreviation P43 FINISHED
Object MTA E147074 NE FINISHED

How this triple was built (2 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: [Maryland Transit Administration, abbreviation, MTA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: MTA
Context triple: [Maryland Transit Administration, abbreviation, MTA]
  • A. MTA chosen
    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 International
    MTA International is a segment of the Italian stock exchange dedicated to the listing and trading of international companies’ shares.
  • E. MTA International
    MTA International is a global, multilingual satellite television network operated by the Ahmadiyya Muslim Community to broadcast religious, educational, and cultural programming worldwide.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69c009043d648190a7af89698ccf1e3e completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c020d82870819087f9591b5a1021ce completed March 22, 2026, 5:03 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0287139508190aa646918228cfdc0 completed March 22, 2026, 5:35 p.m.
Created at: March 22, 2026, 3:38 p.m.