Triple

T2014561
Position Surface form Disambiguated ID Type / Status
Subject Kilchberg Cemetery E43764 entity
Predicate hasGraveOf P196 FINISHED
Object Nelly Mann E235121 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: Nelly Mann | Statement: [Kilchberg Cemetery, hasGraveOf, Nelly Mann]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nelly Mann
Context triple: [Kilchberg Cemetery, hasGraveOf, Nelly Mann]
  • A. Nelly Mann chosen
    Nelly Mann was the wife of German writer Heinrich Mann and sister-in-law of Nobel Prize–winning author Thomas Mann.
  • B. Anita Gütermann
    Anita Gütermann was a German heiress from the Gütermann industrial family who became known as the first wife of renowned conductor Herbert von Karajan.
  • C. Nena von Schlebrügge
    Nena von Schlebrügge is a Swedish-born former fashion model of German and Swedish descent who worked internationally in the 1950s and 1960s and is the mother of actress Uma Thurman.
  • D. Dora Maurer
    Dora Maurer is a Hungarian conceptual artist and filmmaker known for her experimental works exploring perception, movement, and systems-based processes.
  • E. Alma Wassermann
    Alma Wassermann was the wife of Nobel Prize–winning Yiddish author Isaac Bashevis Singer and a significant partner in his personal and literary life.
  • 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_69a88716e9f08190946313fdc949e3cf completed March 4, 2026, 7:25 p.m.
NER Named-entity recognition batch_69abb8b610a88190bc10fd7dda19da08 completed March 7, 2026, 5:33 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae5179b3348190bfec5530baf4ca86 completed March 9, 2026, 4:50 a.m.
Created at: March 4, 2026, 7:37 p.m.