Triple

T9434613
Position Surface form Disambiguated ID Type / Status
Subject Dahme E227470 entity
Predicate tributaryOf P415 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: [Dahme, tributaryOf, Spree]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Spree
Context triple: [Dahme, tributaryOf, 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. Spree
    Spree is a dark satirical horror-thriller film about a rideshare driver obsessed with social media fame, starring Joe Keery.
  • C. Shopify
    Shopify is a leading global e-commerce platform that enables businesses to create and manage online stores and sell products across multiple channels.
  • D. WooCommerce
    WooCommerce is a widely used open-source eCommerce plugin for WordPress that enables users to create and manage online stores.
  • E. Zoho Commerce
    Zoho Commerce is an e-commerce platform that enables businesses to create, manage, and grow online stores with integrated tools for website building, payments, inventory, and order management.
  • 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_69ca8437a7ac81908651de48f2d2141d completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd7e62d53c81908055e0967e6cd54d completed April 1, 2026, 8:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69d122484a90819080e406a7ae5c61fe completed April 4, 2026, 2:38 p.m.
Created at: March 30, 2026, 7:50 p.m.