Triple

T11993008
Position Surface form Disambiguated ID Type / Status
Subject Hanan Townshend E285456 entity
Predicate hasWorkedFor P11675 FINISHED
Object American Express E47812 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: American Express | Statement: [Hanan Townshend, hasWorkedFor, American Express]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: American Express
Context triple: [Hanan Townshend, hasWorkedFor, American Express]
  • A. American Express chosen
    American Express is a global financial services company best known for its charge and credit cards, payment network, and travel-related services.
  • 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. Mastercard
    Mastercard is a global financial services corporation best known for its widely used credit and debit card payment network.
  • D. Diners Club International
    Diners Club International is a global charge card and payment network brand known as one of the world’s first multipurpose payment cards, now owned and operated by Discover Financial Services.
  • E. American Express Green Card
    The American Express Green Card is a travel-focused charge card that earns Membership Rewards points and offers benefits like travel protections and statement credits for frequent travelers.
  • 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_69d6ab44a77c8190a652f4b27164e4ef completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d903b11ac481909866b611380792e7 completed April 10, 2026, 2:05 p.m.
NED1 Entity disambiguation (via context triple) batch_69f49d183ee881908f1c0ca4562344a9 completed May 1, 2026, 12:31 p.m.
Created at: April 8, 2026, 9:46 p.m.