Triple

T5600430
Position Surface form Disambiguated ID Type / Status
Subject Schlossbrücke E147104 entity
Predicate locatedOnWaterway P4361 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: [Schlossbrücke, locatedOnWaterway, Spree]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Spree
Context triple: [Schlossbrücke, locatedOnWaterway, 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. WooCommerce
    WooCommerce is a widely used open-source eCommerce plugin for WordPress that enables users to create and manage online stores.
  • D. Magento
    Magento is an open-source e-commerce platform widely used by businesses to build and manage online stores with extensive customization and scalability.
  • E. Shopian
    Shopian is a town in the southern part of Jammu and Kashmir, India, known historically as an important trading hub and gateway along the ancient Mughal Road.
  • 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_69c009043d648190a7af89698ccf1e3e completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c020d936dc8190a2e599f1df9fdd91 completed March 22, 2026, 5:03 p.m.
NED1 Entity disambiguation (via context triple) batch_69c04d40049881908bf32e4932094c52 completed March 22, 2026, 8:12 p.m.
Created at: March 22, 2026, 3:38 p.m.