Triple

T12019391
Position Surface form Disambiguated ID Type / Status
Subject Dyle E286107 entity
Predicate forms P2100 FINISHED
Object Rupel E97745 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: Rupel | Statement: [Dyle, forms, Rupel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rupel
Context triple: [Dyle, forms, Rupel]
  • A. Rupel chosen
    The Rupel is a short river in northern Belgium that flows through the province of Antwerp and joins the Scheldt near the town of Rupelmonde.
  • B. Dieuze
    Dieuze is a small commune in northeastern France, located in the Moselle department in the historical region of Lorraine.
  • C. River Zenne
    The River Zenne is a small Belgian river that flows through Brussels and surrounding towns, historically shaping the region’s development and urban landscape.
  • D. Waal
    The Waal is a major distributary branch of the Rhine River in the Netherlands, serving as an important waterway for shipping and part of the country’s main river system.
  • E. Meuse
    Meuse is a department in northeastern France known for its rural landscapes and significant World War I battlefields, including Verdun.
  • 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_69d6ab45a368819084fce08bf0dc3705 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d903dabf2c819084dcaa05ae0a6018 completed April 10, 2026, 2:06 p.m.
NED1 Entity disambiguation (via context triple) batch_69f63edddad48190b5b4da184fde27dd completed May 2, 2026, 6:13 p.m.
Created at: April 8, 2026, 9:47 p.m.