Triple

T2136272
Position Surface form Disambiguated ID Type / Status
Subject Brandenburg E46660 entity
Predicate hasRiver P165 FINISHED
Object Spree E34242 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: Spree | Statement: [Brandenburg, hasRiver, Spree]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Spree
Context triple: [Brandenburg, hasRiver, Spree]
  • A. Spree chosen
    The Spree is a major river in eastern Germany that flows through the heart of Berlin and is central to the city's landscape and history.
  • B. WooCommerce
    WooCommerce is a widely used open-source eCommerce plugin for WordPress that enables users to create and manage online stores.
  • C. Magento
    Magento is an open-source e-commerce platform widely used by businesses to build and manage online stores with extensive customization and scalability.
  • D. Stripe
    Stripe is a leading financial technology company that provides online payment processing and related services for internet businesses worldwide.
  • E. Braintree Direct
    Braintree Direct is an online payment processing solution that enables businesses to securely accept and manage credit cards, digital wallets, and other payment methods through web and mobile applications.
  • 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_69a88a174ab48190a5db20c132e5dccf completed March 4, 2026, 7:37 p.m.
NER Named-entity recognition batch_69abbdc4ce8c81908d143d5451681e6a completed March 7, 2026, 5:55 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae51acc0f88190a580e29d887170ec completed March 9, 2026, 4:50 a.m.
Created at: March 4, 2026, 7:44 p.m.