Triple

T12760908
Position Surface form Disambiguated ID Type / Status
Subject WVHA E304990 entity
Predicate officeHolder P537 FINISHED
Object Georg Lörner E656758 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: Georg Lörner | Statement: [WVHA, officeHolder, Georg Lörner]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Georg Lörner
Context triple: [WVHA, officeHolder, Georg Lörner]
  • A. Georg Lörner chosen
    Georg Lörner was a high-ranking SS official and Nazi war criminal who played a key role in the administration of concentration camp economics and was later convicted at the Nuremberg Trials.
  • B. Fritz Loerzer
    Fritz Loerzer was a German military officer and World War II Luftwaffe general.
  • C. Fritz Luchsinger
    Fritz Luchsinger was a Swiss mountaineer best known as one of the first climbers to reach the summit of Lhotse, the world’s fourth-highest mountain.
  • D. Wilhelm Siegling
    Wilhelm Siegling was a German linguist and philologist known for his pioneering work on the Tocharian languages and their classification within the Indo-European language family.
  • E. Otto Kitzler
    Otto Kitzler was a 19th-century Austrian conductor and music teacher best known for mentoring composer Anton Bruckner during his formative years.
  • 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_69d7bdf1fcd081909ffb0e0d6fa3a07d completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d96d8e44188190840cd23d380bf23d completed April 10, 2026, 9:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe64e2991c81908f474fe07a6ba10a completed May 8, 2026, 10:34 p.m.
Created at: April 9, 2026, 5:28 p.m.