Triple

T792320
Position Surface form Disambiguated ID Type / Status
Subject Jürgen Habermas E16940 entity
Predicate residence P75 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: [Jürgen Habermas, residence, Starnberg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Starnberg
Context triple: [Jürgen Habermas, residence, 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 am Lech
    Landsberg am Lech is a historic Bavarian town in southern Germany known for its medieval old town, picturesque setting on the Lech River, and its association with the nearby Landsberg Prison.
  • C. Heidenheim an der Brenz
    Heidenheim an der Brenz is a town in the German state of Baden-Württemberg known for its industrial heritage, historic castle Hellenstein, and location on the Brenz River near the Swabian Jura.
  • D. Boblingen
    Böblingen is a town in the German state of Baden-Württemberg, known for its automotive industry presence and proximity to Stuttgart.
  • E. Sieber
    Sieber is a small river in the German state of Lower Saxony that flows through the Harz Mountains and into the Oder.
  • 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_69a4936cb7448190914f5fe4b8d81607 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4a798c7608190b9c79c52a1fe0859 completed March 1, 2026, 8:54 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac2578477c8190983de0a1065ad8ec completed March 7, 2026, 1:17 p.m.
Created at: March 1, 2026, 7:38 p.m.