Triple

T13306562
Position Surface form Disambiguated ID Type / Status
Subject Gerhart Hauptmann E316949 entity
Predicate residence P75 FINISHED
Object Agnetendorf E1089458 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: Agnetendorf | Statement: [Gerhart Hauptmann, residence, Agnetendorf]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Agnetendorf
Context triple: [Gerhart Hauptmann, residence, Agnetendorf]
  • A. Agnetendorf chosen
    Agnetendorf is a village in present-day Poland (now known as Jagniątków) historically notable as the longtime residence and place of death of Nobel Prize–winning German writer Gerhart Hauptmann.
  • B. Hägendorf
    Hägendorf is a municipality in the canton of Solothurn in northwestern Switzerland, known for its residential character and proximity to the Jura mountains.
  • C. Aulendorf
    Aulendorf is a small town in the Upper Swabia region of southern Germany, known for its historic castle and spa facilities.
  • D. Allendorf
    Allendorf is a village-level subdivision of the town of Sundern in the Hochsauerland district of North Rhine-Westphalia, Germany.
  • E. Hettstadt
    Hettstadt is a small municipality in the Würzburg district of Bavaria, Germany, known for its rural character and proximity to the city of Würzburg.
  • 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_69d806b40ab4819094adf6c374f4811a completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d990a8be108190bad0021f95ce3a93 completed April 11, 2026, 12:07 a.m.
NED1 Entity disambiguation (via context triple) batch_69fd8a9c41908190b789765861bd9924 completed May 8, 2026, 7:02 a.m.
Created at: April 9, 2026, 9:29 p.m.