Triple

T9632089
Position Surface form Disambiguated ID Type / Status
Subject BioNTech E232831 entity
Predicate hasKeyPerson P256 FINISHED
Object Ozlem Tureci E812194 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: Ozlem Tureci | Statement: [BioNTech, hasKeyPerson, Ozlem Tureci]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ozlem Tureci
Context triple: [BioNTech, hasKeyPerson, Ozlem Tureci]
  • A. Ozlem Tureci chosen
    Özlem Türeci is a German physician, scientist, and entrepreneur best known as the co-founder and chief medical officer of BioNTech, where she helped develop one of the first mRNA-based COVID-19 vaccines.
  • B. Feride Karaca
    Feride Karaca is known as the wife of legendary Turkish rock musician and political activist Cem Karaca.
  • C. Emine Sevgi Özdamar
    Emine Sevgi Özdamar is a Turkish-German writer, actress, and director renowned for her innovative German-language prose exploring migration, identity, and intercultural experience.
  • D. Zehra Zümrüt Selçuk
    Zehra Zümrüt Selçuk is a Turkish politician and former Minister of Family, Labour and Social Services known for her work on social policy and welfare issues.
  • E. Nesrin Cansever
    Nesrin Cansever is known as the wife of prominent Turkish modernist poet Edip Cansever.
  • 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_69ca848940cc8190b97cec654cb3bb4a completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd9b2783b48190a9929dc3e3cd2956 completed April 1, 2026, 10:24 p.m.
NED1 Entity disambiguation (via context triple) batch_69d189fa706c819080e8ac2411f57d93 completed April 4, 2026, 10 p.m.
Created at: March 30, 2026, 8:11 p.m.