Triple

T19117485
Position Surface form Disambiguated ID Type / Status
Subject T-money card E467941 entity
Predicate alsoKnownAs P39 FINISHED
Object 티머니 카드
티머니 카드는 서울 및 수도권을 중심으로 대중교통과 편의점 등에서 간편 결제가 가능한 선불·후불 교통카드 겸 전자화폐이다.
E1359248 NE FINISHED

How this triple was built (4 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: 티머니 카드 | Statement: [T-money card, alsoKnownAs, 티머니 카드]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: 티머니 카드
Context triple: [T-money card, alsoKnownAs, 티머니 카드]
  • A. Metcard
    Metcard was Melbourne’s former magnetic stripe ticketing system used for public transport before the introduction of the Myki smartcard.
  • B. Discover Card
    Discover Card is a major U.S. credit card brand known for its cash-back rewards, no annual fees on many cards, and widespread acceptance.
  • C. Apple Card
    Apple Card is a digital-first credit card created by Apple and issued by Goldman Sachs, designed for use with Apple Pay and the Apple Wallet app, offering daily cash-back rewards and strong privacy features.
  • D. Clipper card
    The Clipper card is a reloadable contactless smart card used to pay fares across multiple public transit systems in the San Francisco Bay Area.
  • E. エポスカード
    エポスカードは、丸井グループ系のクレジットカードブランドで、ショッピングや飲食などでのポイント還元や優待特典が充実しているカードサービスです。
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: 티머니 카드
Triple: [T-money card, alsoKnownAs, 티머니 카드]
Generated description
티머니 카드는 서울 및 수도권을 중심으로 대중교통과 편의점 등에서 간편 결제가 가능한 선불·후불 교통카드 겸 전자화폐이다.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: 티머니 카드
Target entity description: 티머니 카드는 서울 및 수도권을 중심으로 대중교통과 편의점 등에서 간편 결제가 가능한 선불·후불 교통카드 겸 전자화폐이다.
  • A. Metcard
    Metcard was Melbourne’s former magnetic stripe ticketing system used for public transport before the introduction of the Myki smartcard.
  • B. Discover Card
    Discover Card is a major U.S. credit card brand known for its cash-back rewards, no annual fees on many cards, and widespread acceptance.
  • C. Apple Card
    Apple Card is a digital-first credit card created by Apple and issued by Goldman Sachs, designed for use with Apple Pay and the Apple Wallet app, offering daily cash-back rewards and strong privacy features.
  • D. Clipper card
    The Clipper card is a reloadable contactless smart card used to pay fares across multiple public transit systems in the San Francisco Bay Area.
  • E. エポスカード
    エポスカードは、丸井グループ系のクレジットカードブランドで、ショッピングや飲食などでのポイント還元や優待特典が充実しているカードサービスです。
  • F. None of above. chosen

Provenance (5 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_69d8dd06a26481908039e2a1bae8c597 completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5e399a6d8819090a9501ff1637b9d completed April 20, 2026, 8:28 a.m.
NED1 Entity disambiguation (via context triple) batch_6a05e671f2988190a74d53989124026b completed May 14, 2026, 3:12 p.m.
NEDg Description generation batch_6a05e9406ba48190a50f4ea6b413e1f4 completed May 14, 2026, 3:24 p.m.
NED2 Entity disambiguation (via description) batch_6a05e9c0d35081909b6ce3c287af5d5f completed May 14, 2026, 3:26 p.m.
Created at: April 10, 2026, 12:05 p.m.