Triple

T2150933
Position Surface form Disambiguated ID Type / Status
Subject Hansdorf, Province of Prussia E47177 entity
Predicate namedAfter P63 FINISHED
Object Hans (personal name) E75878 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: Hans (personal name) | Statement: [Hansdorf, Province of Prussia, namedAfter, Hans (personal name)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hans (personal name)
Context triple: [Hansdorf, Province of Prussia, namedAfter, Hans (personal name)]
  • A. Hans chosen
    Hans is a masculine given name of Germanic origin commonly used in Germanic and Scandinavian countries.
  • B. Georg-Hans
    Georg-Hans is the given name of Georg-Hans Reinhardt, a German general who served in the Wehrmacht during World War II.
  • C. Hans-Jürgen
    Hans-Jürgen is a masculine German given name, typically used as a compound first name combining "Hans" and "Jürgen."
  • D. Johann
    Johann is a given name of Germanic origin commonly used in German-speaking and other European countries.
  • E. Henrik
    Henrik is the given name of the renowned Norwegian mathematician Niels Henrik Abel, known for his pioneering work in algebra and analysis.
  • 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_69a88a1933e0819094f18426ed74180f completed March 4, 2026, 7:38 p.m.
NER Named-entity recognition batch_69abbe4747a0819080e2234f3ea8995f completed March 7, 2026, 5:57 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae58dedd3c8190a876819616903392 completed March 9, 2026, 5:21 a.m.
Created at: March 4, 2026, 7:44 p.m.