Triple

T14345621
Position Surface form Disambiguated ID Type / Status
Subject Rupelmonde E355710 entity
Predicate locatedNearRiver P165 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: [Rupelmonde, locatedNearRiver, Rupel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rupel
Context triple: [Rupelmonde, locatedNearRiver, 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. Oldetrijne
    Oldetrijne is a small village in the municipality of Weststellingwerf in the Dutch province of Friesland.
  • C. Dieuze
    Dieuze is a small commune in northeastern France, located in the Moselle department in the historical region of Lorraine.
  • D. 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.
  • E. Kromme Rijn
    Kromme Rijn is a historic branch of the Rhine River in the Dutch province of Utrecht, known for its scenic landscapes and role in regional water management and navigation.
  • 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_69d82790a7e08190877e2d349b2e8d8e completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de8e8b81bc8190ace2a575faf55cc0 completed April 14, 2026, 6:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe9db810c481908dde925ff90f3fa0 completed May 9, 2026, 2:36 a.m.
Created at: April 10, 2026, 1:14 a.m.