Triple

T7259450
Position Surface form Disambiguated ID Type / Status
Subject Peter Grünberg E159609 entity
Predicate name P16 FINISHED
Object Peter Grünberg E159609 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: Peter Grünberg | Statement: [Peter Grünberg, name, Peter Grünberg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Peter Grünberg
Context triple: [Peter Grünberg, name, Peter Grünberg]
  • A. Peter Grünberg chosen
    Peter Grünberg was a German physicist and Nobel laureate renowned for his discovery of giant magnetoresistance, which revolutionized data storage technology.
  • B. Gerhard H. Brandt
    Gerhard H. Brandt is a film producer best known for his work on the movie "Fedora."
  • C. Manfred Gerlach
    Manfred Gerlach was an East German politician and leader of the Liberal Democratic Party who briefly served as the country’s head of state during the political transition of 1989–1990.
  • D. Reinhold Seeberg
    Reinhold Seeberg was a prominent German Lutheran theologian and church historian known for his influential work on dogmatics and for mentoring figures such as Dietrich Bonhoeffer.
  • E. Gunnar Sommerfeldt
    Gunnar Sommerfeldt was a Danish film director and actor active in the early 20th century, known for his work in Scandinavian silent cinema.
  • 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_69c68838f9948190875fd60b2351230c completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6eac340a0819084015a5fbf7a5539 completed March 27, 2026, 8:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7eed1b5a48190875e9e0bfdc80ae4 completed March 28, 2026, 3:08 p.m.
Created at: March 27, 2026, 2:57 p.m.