Triple

T11231857
Position Surface form Disambiguated ID Type / Status
Subject Charlottenburg-Wilmersdorf E265840 entity
Predicate locatedOn P40 FINISHED
Object River Spree E226997 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: River Spree | Statement: [Charlottenburg-Wilmersdorf, locatedOn, River Spree]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: River Spree
Context triple: [Charlottenburg-Wilmersdorf, locatedOn, River Spree]
  • A. River Spree chosen
    River Spree is a major river flowing through Berlin, Germany, known for shaping the city’s landscape and passing many historic and cultural landmarks.
  • B. Oder-Spree
    Oder-Spree is a rural district in the eastern German state of Brandenburg, known for its lakes, forests, and towns along the Oder and Spree rivers.
  • C. Dahme
    Dahme is a small coastal town on the Baltic Sea in northern Germany, known for its beaches and seaside tourism.
  • D. Dahme
    The Dahme is a river in eastern Germany that flows through Brandenburg and Berlin before joining the Spree.
  • E. Unstrut River
    The Unstrut River is a tributary of the Saale in central Germany, flowing through Thuringia and Saxony-Anhalt and known for its scenic valleys, vineyards, and historic towns.
  • 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_69d6aac656d48190b275efaa7d6074ee completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e9026e1c81909456ac946bbba972 completed April 9, 2026, 5:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6554d0b0081909cc031ff06b796c0 completed May 2, 2026, 7:49 p.m.
Created at: April 8, 2026, 9:30 p.m.