Triple

T3411330
Position Surface form Disambiguated ID Type / Status
Subject ICOCA E71900 entity
Predicate technology P1485 FINISHED
Object FeliCa E49795 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: FeliCa | Statement: [ICOCA, technology, FeliCa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: FeliCa
Context triple: [ICOCA, technology, FeliCa]
  • A. NFC
    The NFC (National Football Conference) is one of the two conferences in the National Football League, comprising 16 teams that compete for a spot in the Super Bowl.
  • B. NFC chosen
    NFC (Near Field Communication) is a short-range wireless communication technology commonly used for contactless payments, data exchange, and device pairing between nearby electronic devices.
  • C. Bilhete Único smart card
    The Bilhete Único smart card is São Paulo’s integrated public transport fare card, allowing seamless, discounted transfers across the city’s metro, bus, and train networks.
  • D. ISO/IEC 14443
    ISO/IEC 14443 is an international standard that defines the protocols and characteristics for contactless proximity smart cards and readers, widely used in applications like public transport and secure identification.
  • E. RFID
    RFID (Radio-Frequency Identification) is a wireless technology that uses electromagnetic fields to automatically identify and track tagged objects, commonly employed in areas like inventory management, access control, and contactless payments.
  • 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_69ad85ac312481909e7027ced1456a9f completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb90a76288190b92ef3b26638cd47 completed March 8, 2026, 5:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69b34bdf81e48190abac8ea645e929ce completed March 12, 2026, 11:27 p.m.
Created at: March 8, 2026, 3:15 p.m.