Triple

T13163342
Position Surface form Disambiguated ID Type / Status
Subject Maria Henriette de La Tour d’Auvergne E312780 entity
Predicate residence P75 FINISHED
Object Sulzbach E924749 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: Sulzbach | Statement: [Maria Henriette de La Tour d’Auvergne, residence, Sulzbach]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sulzbach
Context triple: [Maria Henriette de La Tour d’Auvergne, residence, Sulzbach]
  • A. Sulzbach
    Sulzbach is a district of the town of Gaggenau in the Rastatt district of Baden-Württemberg, Germany.
  • B. Sulzbach chosen
    Sulzbach is a historic town in Bavaria, Germany, known for being the seat of the former County Palatine of Sulzbach.
  • C. Schwarzbach
    Schwarzbach is a river in southwestern Germany that flows through the town of Zweibrücken in the state of Rhineland-Palatinate.
  • D. Breitenbach
    Breitenbach is a municipality in the canton of Solothurn in northwestern Switzerland, known for its location in the Thierstein district near the French border.
  • E. Alpirsbach
    Alpirsbach is a small town in Germany’s Black Forest region, known for its historic Benedictine monastery and traditional Alpirsbacher Klosterbräu brewery.
  • 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_69d806ac3ee081909b2fd27d060aa974 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d98c0a9d348190909fcf45f9d650e4 completed April 10, 2026, 11:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6eaf4cd788190b74cca51b5219bfb completed May 3, 2026, 6:28 a.m.
Created at: April 9, 2026, 9:13 p.m.