Triple

T11245777
Position Surface form Disambiguated ID Type / Status
Subject Sendai, Miyagi, Japan E266198 entity
Predicate twinCity P1072 FINISHED
Object Augsburg, Germany E127006 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: Augsburg, Germany | Statement: [Sendai, Miyagi, Japan, twinCity, Augsburg, Germany]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Augsburg, Germany
Context triple: [Sendai, Miyagi, Japan, twinCity, Augsburg, Germany]
  • A. Würzburg, Germany
    Würzburg, Germany is a historic city in northern Bavaria known for its baroque and rococo architecture, prominent university, and renowned Franconian wine culture.
  • B. Augsburg chosen
    Augsburg is one of Germany’s oldest cities, a historic Bavarian center known for its rich Renaissance heritage and role as a major medieval trading hub.
  • C. Regensburg
    Regensburg is a historic city in southeastern Germany known for its well-preserved medieval old town on the Danube River.
  • D. Saalfeld, Germany
    Saalfeld is a historic town in the German state of Thuringia, known for its well-preserved medieval architecture and scenic location on the Saale River.
  • E. Nördlingen, Germany
    Nördlingen is a historic Bavarian town in southern Germany, notable for its well-preserved medieval walls and its location within a large ancient meteorite crater.
  • 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_69d6aac7953c8190b82caf9d7640fdf9 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e91c045c81908a9024a8aee32f4d completed April 9, 2026, 5:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69e4cc69402c8190be8785f892a41c7b completed April 19, 2026, 12:36 p.m.
Created at: April 8, 2026, 9:31 p.m.