Triple

T4813596
Position Surface form Disambiguated ID Type / Status
Subject Hartmann E107131 entity
Predicate derivedFromGivenName P17 FINISHED
Object Hartmann (given name) E107131 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: Hartmann (given name) | Statement: [Hartmann, derivedFromGivenName, Hartmann (given name)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hartmann (given name)
Context triple: [Hartmann, derivedFromGivenName, Hartmann (given name)]
  • A. Hartmann chosen
    Hartmann is a German surname borne by numerous notable individuals across fields such as music, philosophy, and aviation.
  • B. Hans-Jürgen
    Hans-Jürgen is a masculine German given name, typically used as a compound first name combining "Hans" and "Jürgen."
  • C. Hansi
    Hansi is a historic town in the Hisar district of Haryana, India, known for its ancient forts and archaeological significance.
  • D. Helmut
    Helmut is a masculine given name of German origin, historically common in German-speaking countries.
  • E. Heimrich
    Heimrich is a Germanic given name of medieval origin, related to names like Heinrich and Henrik and historically borne by various nobles and notable figures in German-speaking regions.
  • 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_69bd43f779448190b92885cb70abb6c2 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd6c80ce048190a7c9f14431d7c62f completed March 20, 2026, 3:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69be4db1b67c81908272d8b7e7e4e1f1 completed March 21, 2026, 7:50 a.m.
Created at: March 20, 2026, 1:23 p.m.