Triple

T9171257
Position Surface form Disambiguated ID Type / Status
Subject Hanover–Brunswick–Göttingen–Wolfsburg Metropolitan Region E220084 entity
Predicate containsCity P294 FINISHED
Object Gifhorn E217943 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: Gifhorn | Statement: [Hanover–Brunswick–Göttingen–Wolfsburg Metropolitan Region, containsCity, Gifhorn]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gifhorn
Context triple: [Hanover–Brunswick–Göttingen–Wolfsburg Metropolitan Region, containsCity, Gifhorn]
  • A. Gifhorn chosen
    Gifhorn is a town in Lower Saxony, Germany, known for its location near the confluence of several rivers and its historic windmill museum.
  • B. Northeim
    Northeim is a town in Lower Saxony, Germany, known for its medieval old town and location in the Leine River valley.
  • C. Hagen
    Hagen is a city in the Ruhr region of North Rhine-Westphalia in western Germany, known historically as an industrial and transport hub.
  • D. Hagen
    Hagen is a surname of German origin borne by various notable individuals across fields such as music, sports, and academia.
  • E. Gevelsberg
    Gevelsberg is a town in North Rhine-Westphalia, Germany, situated in the Ennepe-Ruhr district within the Ruhr metropolitan region.
  • 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_69ca83e467108190abcae6a33b3d4dad completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69ccaae38ee48190bf783477bc37913d completed April 1, 2026, 5:19 a.m.
NED1 Entity disambiguation (via context triple) batch_69d09b7f95f88190af9c88105abb2964 completed April 4, 2026, 5:02 a.m.
Created at: March 30, 2026, 7:22 p.m.