Triple

T6073000
Position Surface form Disambiguated ID Type / Status
Subject Amboise E135329 entity
Predicate twinTown P1072 FINISHED
Object Füssen E372327 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: Füssen | Statement: [Amboise, twinTown, Füssen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Füssen
Context triple: [Amboise, twinTown, Füssen]
  • A. Füssen chosen
    Füssen is a picturesque Bavarian town in southern Germany, known for its historic old town, proximity to Neuschwanstein Castle, and scenic location near the Alps.
  • B. Kempten
    Kempten is a historic town in Bavaria, Germany, considered one of the country’s oldest urban settlements and known for its location in the Allgäu region.
  • C. Rosenheim
    Rosenheim is a town in Upper Bavaria, Germany, known as a regional economic and transportation hub near the Alps.
  • D. Wolfratshausen
    Wolfratshausen is a Bavarian town in southern Germany known for its historic old town, riverside setting on the Loisach and Isar, and proximity to Munich and the Alps.
  • E. Traunstein
    Traunstein is a town in southeastern Bavaria, Germany, known as a regional administrative and cultural center near the Chiemsee and the Alps.
  • 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_69c00879e8048190b690717d19c5bc03 completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c05759d29481908912015e734ab943 completed March 22, 2026, 8:55 p.m.
NED1 Entity disambiguation (via context triple) batch_69c93a3a7cbc8190a7f183d8a5bb4b06 completed March 29, 2026, 2:42 p.m.
Created at: March 22, 2026, 4:11 p.m.