Triple

T9111486
Position Surface form Disambiguated ID Type / Status
Subject Vergangenes und Gegenwärtiges E218610 entity
Predicate author P4 FINISHED
Object Monika Mann E42635 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: Monika Mann | Statement: [Vergangenes und Gegenwärtiges, author, Monika Mann]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Monika Mann
Context triple: [Vergangenes und Gegenwärtiges, author, Monika Mann]
  • A. Monika Mann chosen
    Monika Mann was a German writer and essayist, best known as one of the literary Nobel laureate Thomas Mann’s daughters and a member of the prominent Mann family of intellectuals.
  • B. Nikita Gill
    Nikita Gill is a contemporary British-Indian poet and writer known for her emotionally resonant, feminist poetry and modern retellings of myths and fairy tales.
  • C. Kajal Gupta
    Kajal Gupta is an actress known for her work in Tollywood, the Bengali-language film industry based in Kolkata.
  • D. Mona Kapoor
    Mona Kapoor was an Indian television and film producer best known as the first wife of Bollywood film producer Boney Kapoor and mother of actor Arjun Kapoor.
  • E. Annet Mahendru
    Annet Mahendru is an American actress best known for her acclaimed role as Nina Sergeevna Krilova on the television series "The Americans."
  • 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_69ca83dc94ac8190b9ef42684d36ff39 completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69cca8495c448190b9bb3803fb2dda70 completed April 1, 2026, 5:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69d047afbc388190905b13582cd59b05 completed April 3, 2026, 11:05 p.m.
Created at: March 30, 2026, 7:16 p.m.