Triple

T2764741
Position Surface form Disambiguated ID Type / Status
Subject MTA New York City Bus E61307 entity
Predicate hasOperatorCode P38995 FINISHED
Object MTAB
MTAB is the operator code used to identify the MTA New York City Bus division within the Metropolitan Transportation Authority’s transit operations.
 E297972 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: MTAB | Statement: [MTA New York City Bus, hasOperatorCode, MTAB]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: MTAB
Context triple: [MTA New York City Bus, hasOperatorCode, MTAB]
  • A. MAB
    MAB is a German bibliographic data format used for cataloging and exchanging library records, closely related to and historically aligned with MARC standards.
  • B. MTPD
    MTPD is the law enforcement agency responsible for policing the Washington Metropolitan Area Transit Authority’s transit system, including Metrorail and Metrobus.
  • C. MTD
    MTD is the public bus transit agency serving the Champaign–Urbana metropolitan area in Illinois.
  • D. .mt
    .mt is the country code top-level domain (ccTLD) assigned to Malta for use on the internet.
  • E. MATE
    MATE is a lightweight, traditional-style desktop environment for Unix-like operating systems, derived from GNOME 2 and focused on simplicity and low resource usage.
  • 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: MTAB
Triple: [MTA New York City Bus, hasOperatorCode, MTAB]
Generated description
MTAB is the operator code used to identify the MTA New York City Bus division within the Metropolitan Transportation Authority’s transit operations.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: MTAB
Target entity description: MTAB is the operator code used to identify the MTA New York City Bus division within the Metropolitan Transportation Authority’s transit operations.
  • A. MAB
    MAB is a German bibliographic data format used for cataloging and exchanging library records, closely related to and historically aligned with MARC standards.
  • B. MTPD
    MTPD is the law enforcement agency responsible for policing the Washington Metropolitan Area Transit Authority’s transit system, including Metrorail and Metrobus.
  • C. MTD
    MTD is the public bus transit agency serving the Champaign–Urbana metropolitan area in Illinois.
  • D. .mt
    .mt is the country code top-level domain (ccTLD) assigned to Malta for use on the internet.
  • E. MATE
    MATE is a lightweight, traditional-style desktop environment for Unix-like operating systems, derived from GNOME 2 and focused on simplicity and low resource usage.
  • 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_69ab4b7bab6c8190a5c2efef19a8ef34 completed March 6, 2026, 9:47 p.m.
NER Named-entity recognition batch_69abe0895e5881909702e69aaee5c425 completed March 7, 2026, 8:23 a.m.
NED1 Entity disambiguation (via context triple) batch_69afc048bc8481908a6f70e034167c2a completed March 10, 2026, 6:55 a.m.
NEDg Description generation batch_69afc14239e48190ad20f660e88befcb completed March 10, 2026, 6:59 a.m.
NED2 Entity disambiguation (via description) batch_69afc202466c81908c300520173837dc completed March 10, 2026, 7:02 a.m.
Created at: March 6, 2026, 9:57 p.m.