Triple

T5372055
Position Surface form Disambiguated ID Type / Status
Subject Helmscherode E108872 entity
Predicate locatedIn P40 FINISHED
Object 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: Einbeck | Statement: [Helmscherode, locatedIn, Einbeck]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Einbeck
Context triple: [Helmscherode, locatedIn, Einbeck]
  • A. Einbeck chosen
    Einbeck is a historic town in Lower Saxony, Germany, renowned for its medieval architecture and traditional beer brewing.
  • B. Nordhausen
    Nordhausen is a historic town in central Germany known for its medieval architecture, former role as a key trading center, and association with the nearby Mittelbau-Dora concentration camp site.
  • C. Saalfeld
    Saalfeld is a town in the German state of Thuringia, known for its historic old town and former significance as a regional railway and industrial center.
  • D. Merseburg
    Merseburg is a historic town in the German state of Saxony-Anhalt, known for its medieval cathedral and role as an important cultural and administrative center on the River Saale.
  • E. Halberstadt
    Halberstadt is a historic town in the German state of Saxony-Anhalt, known for its medieval architecture and role as a former episcopal seat.
  • 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_69bd440c77948190aad2a5f39b7b80f5 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd86aa0f5c8190ba96554e75696f8e completed March 20, 2026, 5:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69bfabe6de448190a4e0c2e537a2e045 completed March 22, 2026, 8:44 a.m.
Created at: March 20, 2026, 2:02 p.m.