Triple

T7624556
Position Surface form Disambiguated ID Type / Status
Subject Erft River E172592 entity
Predicate nameInGerman P22792 FINISHED
Object Erft E172592 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: Erft | Statement: [Erft River, nameInGerman, Erft]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Erft
Context triple: [Erft River, nameInGerman, Erft]
  • A. Erft River chosen
    The Erft River is a tributary of the Rhine in western Germany, flowing through North Rhine-Westphalia and known for passing historic towns and former mining areas before joining the Rhine near Neuss.
  • B. Rheine
    Rheine is a German city in the state of North Rhine-Westphalia, known for its historical town center and location along the River Ems.
  • C. Roer
    The Roer is a river in Western Europe that flows through parts of Belgium, Germany, and the Netherlands before joining the Meuse.
  • D. Rhein II
    Rhein II is a large-scale color photograph by German visual artist Andreas Gursky, renowned for its minimalist depiction of the Rhine River and for once being the most expensive photograph ever sold at auction.
  • E. Rhens
    Rhens is a historic town on the Rhine River in western Germany, known for its medieval role as a meeting place of the prince-electors of the Holy Roman Empire.
  • 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_69c699517e348190bd3348b6889200f2 completed March 27, 2026, 2:50 p.m.
NER Named-entity recognition batch_69c6fa6648608190a9203b98b76209aa completed March 27, 2026, 9:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69c9742fd0dc8190a154cf83c87eb508 completed March 29, 2026, 6:49 p.m.
Created at: March 27, 2026, 3:56 p.m.