Triple

T10493567
Position Surface form Disambiguated ID Type / Status
Subject Ferdinand Steiner E247477 entity
Predicate hasFamilyName P18 FINISHED
Object Steiner E144974 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: Steiner | Statement: [Ferdinand Steiner, hasFamilyName, Steiner]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Steiner
Context triple: [Ferdinand Steiner, hasFamilyName, Steiner]
  • A. Steiner chosen
    Steiner is a common German-language surname borne by numerous notable individuals across fields such as music, philosophy, and science.
  • B. Shteiner
    Shteiner is an alternative spelling or transliteration of the surname Steiner, which is of German origin and borne by various notable individuals.
  • C. Steiner Tor
    Steiner Tor is a historic city gate and iconic symbol of Krems an der Donau in Lower Austria, dating back to the medieval fortifications of the town.
  • D. Stüler
    Stüler is the surname of Friedrich August Stüler, a prominent 19th-century Prussian architect known for his neoclassical and neo-Renaissance designs.
  • E. Hufstedler
    Hufstedler is the surname of Shirley Hufstedler, a prominent American judge and the first U.S. Secretary of Education.
  • 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_69d381c309b88190af78aa681cf6a4c2 completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d5097fe2bc81909d66ce43f3533284 completed April 7, 2026, 1:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69d90dd040f48190a645ebd131f9205c completed April 10, 2026, 2:48 p.m.
Created at: April 6, 2026, 12:24 p.m.