Triple

T15645290
Position Surface form Disambiguated ID Type / Status
Subject MRT E376161 entity
Predicate smartCardSystem P35327 FINISHED
Object iPASS E376163 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: iPASS | Statement: [MRT, smartCardSystem, iPASS]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: iPASS
Context triple: [MRT, smartCardSystem, iPASS]
  • A. iPASS chosen
    iPASS is a Taiwanese contactless smart card widely used for public transportation fares and small-value electronic payments.
  • B. I-PASS
    I-PASS is an electronic toll collection system used on Illinois tollways that allows drivers to pay tolls automatically without stopping.
  • C. PASPA
    PASPA was a 1992 U.S. federal law that effectively banned state-authorized sports betting nationwide until it was struck down by the Supreme Court in 2018.
  • D. OnePass
    OnePass was Continental Airlines’ frequent flyer loyalty program that allowed passengers to earn and redeem miles for flights and travel rewards.
  • E. Telepass
    Telepass is an Italian electronic toll collection system that allows drivers to pay motorway and other transport-related fees automatically without stopping at toll booths.
  • 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_69d85cd1564c8190991adda63bfab4b0 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04ed400ec8190a14a9f7cf3092865 completed April 16, 2026, 2:52 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff5f4e558481909a39fdc5d104994a completed May 9, 2026, 4:22 p.m.
Created at: April 10, 2026, 4:15 a.m.