Triple

T14227863
Position Surface form Disambiguated ID Type / Status
Subject Haus Welf E352669 entity
Predicate istHerkunftsregion P70557 FINISHED
Object Bayern E7752 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: Bayern | Statement: [Haus Welf, istHerkunftsregion, Bayern]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bayern
Context triple: [Haus Welf, istHerkunftsregion, Bayern]
  • A. Bavaria chosen
    Bavaria is a historic region and federal state in southeastern Germany, known for its distinct cultural traditions, large size and population, and major cities such as Munich.
  • B. Baier
    Baier is a surname most prominently associated with Bret Baier, the American television news anchor and host on Fox News.
  • C. Swabia (Bavaria)
    Swabia (Bavaria) is an administrative region in southwestern Bavaria, Germany, known for its distinct Swabian cultural heritage and mix of industrial cities and rural landscapes.
  • D. Bavier
    Bavier is the surname of Frances Bavier, the American actress best known for playing Aunt Bee on the classic television series "The Andy Griffith Show."
  • E. Hesse
    Hesse is a federal state in central Germany known for its financial hub Frankfurt am Main and its mix of urban centers, forests, and historic towns.
  • 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_69d8278adc7c8190a9218d69bce3c4e6 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de622a48508190bbfedb762bd1674d completed April 14, 2026, 3:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd281801488190bcb17d27ee18cde6 completed May 8, 2026, 12:02 a.m.
Created at: April 10, 2026, 1:07 a.m.