Triple

T11679902
Position Surface form Disambiguated ID Type / Status
Subject Katipunan station E277587 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: [Katipunan station, fareSystem, Beep card]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Beep card
Context triple: [Katipunan 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_69d6aafd0a448190b44da30af8c6c519 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8a461b0908190bef4e1c6777affcf completed April 10, 2026, 7:18 a.m.
NED1 Entity disambiguation (via context triple) batch_69f0192f790c8190a99d512b6f5c15aa completed April 28, 2026, 2:19 a.m.
Created at: April 8, 2026, 9:40 p.m.