Triple

T2777556
Position Surface form Disambiguated ID Type / Status
Subject Göttingen district E61609 entity
Predicate hasLandscape P940 FINISHED
Object Solling E229268 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: Solling | Statement: [Göttingen district, hasLandscape, Solling]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Solling
Context triple: [Göttingen district, hasLandscape, Solling]
  • A. Solling chosen
    Solling is a forested low mountain range in Lower Saxony, Germany, known for its extensive woodlands and role as a major part of the Weser Uplands.
  • B. Kellerwald
    Kellerwald is a low mountain forest region in central Germany known for its ancient beech woodlands and protected national park status.
  • C. Eschwege
    Eschwege is a small historic town in the German state of Hesse, known for its medieval architecture and location near the Werra River.
  • D. Rheydt
    Rheydt is a district of the German city of Mönchengladbach in North Rhine-Westphalia, historically an independent town in the Rhineland.
  • E. Wiehe
    Wiehe is a small town in the German state of Thuringia, historically notable as the birthplace of the influential 19th-century historian Leopold von Ranke.
  • 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_69ab4b7e43c48190997b8fc8fb1663ab completed March 6, 2026, 9:47 p.m.
NER Named-entity recognition batch_69abdd82a864819082bd1181a16d5208 completed March 7, 2026, 8:10 a.m.
NED1 Entity disambiguation (via context triple) batch_69afe8a126f881909c378eca59b570a0 completed March 10, 2026, 9:47 a.m.
Created at: March 6, 2026, 9:57 p.m.