Triple

T15100034
Position Surface form Disambiguated ID Type / Status
Subject Einhard E360638 entity
Predicate residence P75 FINISHED
Object Seligenstadt E446520 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: Seligenstadt | Statement: [Einhard, residence, Seligenstadt]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Seligenstadt
Context triple: [Einhard, residence, Seligenstadt]
  • A. Seligenstadt chosen
    Seligenstadt is a historic town in Hesse, Germany, known for its well-preserved medieval center and its association with the Carolingian scholar Einhard.
  • B. Johanngeorgenstadt
    Johanngeorgenstadt is a historic mining town in Germany’s Ore Mountains known for its rich folk traditions and craftsmanship, especially in woodcarving and Christmas-related arts.
  • C. Rudolstadt
    Rudolstadt is a historic town in the German state of Thuringia, known for its picturesque old town, Heidecksburg Castle, and cultural festivals.
  • D. Augustdorf
    Augustdorf is a municipality in North Rhine-Westphalia, Germany, known for its proximity to the Teutoburg Forest and its significant military presence, including Bundeswehr facilities.
  • E. Jüterbog
    Jüterbog is a historic town in the German state of Brandenburg, known for its medieval architecture and long-standing cultural heritage.
  • 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_69d85a035aa88190b52a139d3a1b7b6d completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e00550007481909e02ee1d597a4d37 completed April 15, 2026, 9:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69fffee31b70819092d0583100a7101a completed May 10, 2026, 3:43 a.m.
Created at: April 10, 2026, 3:04 a.m.