Triple

T9505938
Position Surface form Disambiguated ID Type / Status
Subject Solling E229268 entity
Predicate locatedNear P294 FINISHED
Object city of Einbeck E525875 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: city of Einbeck | Statement: [Solling, locatedNear, city of Einbeck]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: city of Einbeck
Context triple: [Solling, locatedNear, city of Einbeck]
  • A. Einbeck chosen
    Einbeck is a historic town in Lower Saxony, Germany, renowned for its medieval architecture and traditional beer brewing.
  • B. Stadt Ahaus
    Stadt Ahaus is a town in the district of Borken in North Rhine-Westphalia, Germany, known for its historic castle and proximity to the Dutch border.
  • C. Imperial City of Soest
    The Imperial City of Soest was a significant medieval free imperial city in present-day North Rhine-Westphalia, Germany, known for its strategic location and economic importance in the Holy Roman Empire.
  • D. Hildesheim
    Hildesheim is a historic city in northern Germany renowned for its medieval architecture and UNESCO-listed Romanesque churches.
  • E. Nienburg
    Nienburg is a historic town in Lower Saxony, Germany, known for its medieval architecture and scenic location along the Weser River.
  • 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_69ca847611c48190a28c028644198c75 completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd9852b7e48190a8f69cbde10d2858 completed April 1, 2026, 10:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69d13a1de2d88190a6a10379d2297510 completed April 4, 2026, 4:19 p.m.
Created at: March 30, 2026, 7:57 p.m.