Triple

T706260
Position Surface form Disambiguated ID Type / Status
Subject E train E14105 entity
Predicate serviceLetter P3497 FINISHED
Object E E5353 NE FINISHED

How this triple was built (3 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: E | Statement: [E train, serviceLetter, E]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: E
Context triple: [E train, serviceLetter, E]
  • A. E chosen
    The E is a New York City Subway line that runs between Queens and Manhattan, providing a key rapid transit connection used by AirTrain JFK passengers traveling to and from the city.
  • B. EC
    EC is the two-letter ISO 3166-1 alpha-2 country code assigned to Ecuador.
  • C. ED
    ED is the federal agency responsible for establishing policy, administering, and coordinating most education-related programs in the United States.
  • D. EG
    EG is the standard abbreviation for the Egmont Group, an international network of Financial Intelligence Units that collaborates to combat money laundering and terrorist financing.
  • E. D
    D is a statically typed, compiled systems programming language designed as a modern successor to C and C++, emphasizing high performance, safety features, and programmer productivity.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: serviceLetter
Context triple: [E train, serviceLetter, E]
  • A. usesLetteredServices chosen
    Indicates that an entity makes use of services that are identified or categorized by letter-based designations.
  • B. serviceWith
    Indicates that one entity provides or is associated with a particular service offered to or used by another entity.
  • C. serviceNumber
    Indicates a unique identifying number assigned to a service, used to reference, track, or distinguish that service from others.
  • D. serviceOf
    Indicates that one entity performs, provides, or fulfills a function or duty on behalf of another entity.
  • E. service
    Indicates that one entity performs work, assistance, or functions to meet the needs or requests of another entity.
  • F. None of above.

Provenance (4 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_69a493494ec48190ae6751683625a9ba completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4a58d4c3c8190ad4527d14bca5e6e completed March 1, 2026, 8:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69a5dcb1795c8190a178e14509b8b271 completed March 2, 2026, 6:53 p.m.
PD Predicate disambiguation batch_69a4a4edc33881909a978268f6dd5d82 completed March 1, 2026, 8:43 p.m.
Created at: March 1, 2026, 7:36 p.m.