Triple

T21300260
Position Surface form Disambiguated ID Type / Status
Subject A39 motorway E525040 entity
Predicate passesNear P416 FINISHED
Object Gifhorn NE NERFINISHED

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: [A39 motorway, passesNear, Gifhorn]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gifhorn
Context triple: [A39 motorway, passesNear, 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. Hagen
    Hagen is a formidable and cunning warrior in the medieval German epic "Nibelungenlied," best known for betraying and killing the hero Siegfried.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b517e6748190850d6f6ddf323d69 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e7385b1c548190b940ded0163ee3ca completed April 21, 2026, 8:42 a.m.
Created at: April 16, 2026, 4:05 p.m.