Triple

T14631727
Position Surface form Disambiguated ID Type / Status
Subject North Avenue station E343493 entity
Predicate fareSystem P395 FINISHED
Object Beep card E940545 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: Beep card | Statement: [North Avenue station, fareSystem, Beep card]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Beep card
Context triple: [North Avenue station, fareSystem, Beep card]
  • A. Beep card chosen
    The Beep card is a contactless smart card used as a stored-value ticketing system for public transportation and related services in the Philippines.
  • B. Leap Card
    Leap Card is a reusable, contactless smart card used for paying public transport fares across Dublin and other parts of Ireland.
  • C. BEEP
    BEEP (Blocks Extensible Exchange Protocol) is a generic application protocol framework that provides a standardized way to structure and manage asynchronous, message-oriented communications over a network.
  • D. Pronto card
    The Pronto card is a reloadable smart fare card used for paying public transit fares across the San Diego Metropolitan Transit System and related services.
  • E. Bip! card
    The Bip! card is a rechargeable contactless smart card used to pay fares across Santiago, Chile’s integrated public transportation system.
  • 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_69d822dffc3c8190aa173b90761bffda completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb4a912248190a3df7f821395c776 completed April 14, 2026, 9:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69fda931834081909d90ec0479eca3f9 completed May 8, 2026, 9:13 a.m.
Created at: April 10, 2026, 1:26 a.m.