Triple

T9146366
Position Surface form Disambiguated ID Type / Status
Subject Starnberg railway station E219465 entity
Predicate locatedIn P40 FINISHED
Object Starnberg E42787 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: Starnberg | Statement: [Starnberg railway station, locatedIn, Starnberg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Starnberg
Context triple: [Starnberg railway station, locatedIn, Starnberg]
  • A. Starnberg chosen
    Starnberg is a lakeside town in Bavaria, Germany, known for its affluent residential character and scenic location on Lake Starnberg southwest of Munich.
  • B. Landsberg
    Landsberg is a town in the Saalekreis district of the German state of Saxony-Anhalt.
  • C. Dornstadt
    Dornstadt is a municipality in the Alb-Donau district of Baden-Württemberg in southern Germany, located near the city of Ulm.
  • D. Idstein
    Idstein is a historic town in the German state of Hesse, known for its well-preserved medieval old town and timber-framed architecture.
  • E. Brackenheim
    Brackenheim is a small town in the German state of Baden-Württemberg, best known as the birthplace of Theodor Heuss, the first President of the Federal Republic of Germany.
  • 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_69ca83e121dc81909912bd66953081c5 completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69cca917914c8190b97ca9169bbd1e5e completed April 1, 2026, 5:11 a.m.
NED1 Entity disambiguation (via context triple) batch_69d09b75186c8190849f86b7e26093f1 completed April 4, 2026, 5:02 a.m.
Created at: March 30, 2026, 7:20 p.m.