Triple

T4717768
Position Surface form Disambiguated ID Type / Status
Subject Hendrik E104689 entity
Predicate etymologicalRoot P453 FINISHED
Object Heimrich E339207 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: Heimrich | Statement: [Hendrik, etymologicalRoot, Heimrich]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Heimrich
Context triple: [Hendrik, etymologicalRoot, Heimrich]
  • A. Heimrich chosen
    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.
  • B. Heimberger
    Heimberger is the original surname of American actor Eddie Albert, best known for his role in the television series "Green Acres."
  • C. Heinrici
    Heinrici is a German surname most notably associated with Gotthard Heinrici, a senior Wehrmacht general during World War II.
  • D. Heurich
    Heurich is a German surname most notably associated with Christian Heurich, a prominent brewer and businessman in Washington, D.C.
  • E. Hansi
    Hansi is a historic town in the Hisar district of Haryana, India, known for its ancient forts and archaeological significance.
  • 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_69bd43ec4a348190bc41afae43375e71 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd64261af08190b0d5d86b0e7bacc0 completed March 20, 2026, 3:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69be1088103c819098296ce700697e90 completed March 21, 2026, 3:29 a.m.
Created at: March 20, 2026, 1:18 p.m.