Triple

T14185695
Position Surface form Disambiguated ID Type / Status
Subject Rotterdam Metro E351568 entity
Predicate terminus P388 FINISHED
Object De Akkers E351567 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: De Akkers | Statement: [Rotterdam Metro, terminus, De Akkers]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: De Akkers
Context triple: [Rotterdam Metro, terminus, De Akkers]
  • A. De Akkers chosen
    De Akkers is a metro station in Spijkenisse, Netherlands, serving as a terminus on the Rotterdam Metro network.
  • B. Oversticht
    Oversticht was a medieval territorial region in the northern Low Countries that roughly corresponds to much of the modern Dutch province of Overijssel and surrounding areas.
  • C. Dorp aan de rivier
    Dorp aan de rivier is a 1958 Dutch drama film directed by Fons Rademakers, regarded as a classic of Dutch cinema and one of the country's early internationally acclaimed films.
  • D. De Waterkant
    De Waterkant is a trendy, historic neighborhood in Cape Town known for its cobbled streets, colorful cottages, and vibrant café and nightlife scene.
  • E. De Koperwiek
    De Koperwiek is a major shopping center in Capelle aan den IJssel, Netherlands, featuring a variety of retail stores, services, and dining options.
  • 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_69d8278834a08190b0f1784e58d7b99c completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de61cd5778819092a03597bcdcc182 completed April 14, 2026, 3:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd19433dc08190b4d2f1aef1b2d67d completed May 7, 2026, 10:59 p.m.
Created at: April 10, 2026, 1:03 a.m.