Triple

T8962280
Position Surface form Disambiguated ID Type / Status
Subject Landkreis Sigmaringen E214035 entity
Predicate contains P35 FINISHED
Object town of Bad Saulgau E727131 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: town of Bad Saulgau | Statement: [Landkreis Sigmaringen, contains, town of Bad Saulgau]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: town of Bad Saulgau
Context triple: [Landkreis Sigmaringen, contains, town of Bad Saulgau]
  • A. Bad Saulgau chosen
    Bad Saulgau is a spa town in the district of Sigmaringen in Baden-Württemberg, Germany, known for its thermal baths and historic town center.
  • B. Bad Salzungen
    Bad Salzungen is a spa town in Thuringia, Germany, known for its saline springs and therapeutic health resorts.
  • C. Bad Reichenhall
    Bad Reichenhall is a Bavarian spa town in southeastern Germany, renowned for its alpine setting and historic salt production.
  • D. Schongau
    Schongau is a historic Bavarian town in southern Germany known for its well-preserved medieval old town and location along the Romantic Road.
  • E. Bad Säckingen
    Bad Säckingen is a historic spa town in southwestern Germany on the Rhine River, known for its medieval old town and one of the longest covered wooden bridges in Europe.
  • 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_69ca839cd6008190a1546a701a56710c completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc6749e5008190a01f42a2e772dd54 completed April 1, 2026, 12:31 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfc94e088881909506b229d1fff44a completed April 3, 2026, 2:06 p.m.
Created at: March 30, 2026, 7:01 p.m.