Triple

T891740
Position Surface form Disambiguated ID Type / Status
Subject Heinrich Hertz E19253 entity
Predicate givenName P17 FINISHED
Object Heinrich E70531 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: Heinrich | Statement: [Heinrich Hertz, givenName, Heinrich]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Heinrich
Context triple: [Heinrich Hertz, givenName, Heinrich]
  • A. Heinrich chosen
    Heinrich is a masculine given name of German origin that has been borne by numerous historical figures, including nobility, scholars, and political leaders.
  • B. Hermann
    Hermann Minkowski was a German mathematician best known for developing the geometric formulation of special relativity using four-dimensional spacetime.
  • C. Gustav
    Gustav is a masculine given name of German origin, borne by several notable historical figures including scientists, artists, and royalty.
  • D. Wilhelm
    Wilhelm is a Germanic given name, equivalent to William, historically borne by numerous European nobles, rulers, and notable figures.
  • E. Werner
    Werner is a given name and surname of Germanic origin, commonly used in German-speaking countries.
  • 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_69a4939d37188190848be3d426ebc9ae completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4ad019e448190ab991e85dc6d7708 completed March 1, 2026, 9:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69acd46627dc81908565f4f93cd35012 completed March 8, 2026, 1:44 a.m.
Created at: March 1, 2026, 7:39 p.m.