Triple

T4667770
Position Surface form Disambiguated ID Type / Status
Subject Rolf Zinkernagel E102888 entity
Predicate familyName P18 FINISHED
Object Zinkernagel E102888 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: Zinkernagel | Statement: [Rolf Zinkernagel, familyName, Zinkernagel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Zinkernagel
Context triple: [Rolf Zinkernagel, familyName, Zinkernagel]
  • A. Zinkernagel chosen
    Zinkernagel is a Swiss surname most notably borne by immunologist Rolf Zinkernagel, co-recipient of the 1996 Nobel Prize in Physiology or Medicine.
  • B. Kritzinger
    Kritzinger is a German surname most notably associated with Friedrich Wilhelm Kritzinger, a high-ranking Nazi official involved in the administrative planning of the Holocaust.
  • C. Ziegelstein
    Ziegelstein is a district in Nuremberg, Germany, known for its residential character and proximity to Nuremberg Airport.
  • D. Zurer
    Zurer is the surname of Ayelet Zurer, an Israeli actress known for her roles in international films and television series.
  • E. Klamm
    Klamm is a powerful, elusive bureaucratic official in Franz Kafka’s novel "The Castle," symbolizing opaque and inaccessible authority.
  • 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_69bd43d9cba4819086c1ab1c2d9d2133 completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd633ec8b08190bf8ffd4c3b946f61 completed March 20, 2026, 3:09 p.m.
NED1 Entity disambiguation (via context triple) batch_69be038912488190a109d4ce624b813d completed March 21, 2026, 2:33 a.m.
Created at: March 20, 2026, 1:15 p.m.