Triple

T1193293
Position Surface form Disambiguated ID Type / Status
Subject Göttingen E25610 entity
Predicate locatedOn P40 FINISHED
Object Leine River E35561 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: Leine River | Statement: [Göttingen, locatedOn, Leine River]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Leine River
Context triple: [Göttingen, locatedOn, Leine River]
  • A. Leine chosen
    The Leine is a major river in central Germany that flows through the federal state of Lower Saxony, passing cities such as Göttingen and Hanover before joining the Aller.
  • B. Erft River
    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.
  • C. Lippe
    Lippe is a historical region in northwestern Germany that once formed a small principality and later a Free State within the German Reich.
  • D. Lippe
    The Lippe is a river in western Germany that flows through North Rhine-Westphalia and is a right-bank tributary of the Rhine.
  • E. Roer
    The Roer is a river in Western Europe that flows through parts of Belgium, Germany, and the Netherlands before joining the Meuse.
  • 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_69a49429f5ec8190a6a205eb0ae81e5e completed March 1, 2026, 7:31 p.m.
NER Named-entity recognition batch_69a4bd761ef08190b431b80f326d1ab2 completed March 1, 2026, 10:28 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad718af9a08190b16c7df72d1ef1d3 completed March 8, 2026, 12:54 p.m.
Created at: March 1, 2026, 7:46 p.m.