Triple

T4243039
Position Surface form Disambiguated ID Type / Status
Subject Frits Zernike E95460 entity
Predicate givenName P17 FINISHED
Object Frits E351549 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: Frits | Statement: [Frits Zernike, givenName, Frits]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Frits
Context triple: [Frits Zernike, givenName, Frits]
  • A. Frits chosen
    Frits is a Dutch given name most notably borne by Frits Bolkestein, a prominent Dutch politician and former European Commissioner.
  • B. Marius de Vries
    Marius de Vries is a British composer, producer, and arranger known for his innovative work on film soundtracks and collaborations with prominent pop and electronic artists.
  • C. Martin Rythovius
    Martin Rythovius was a 16th-century Roman Catholic bishop known for his leadership of the Diocese of Ypres during the turbulent period of the Reformation in the Habsburg Netherlands.
  • D. Fritz ter Meer
    Fritz ter Meer was a German chemist, industrialist, and Nazi-era executive who served as a leading figure at IG Farben and was later convicted at the Nuremberg Trials for his role in war crimes.
  • E. Victor Francen
    Victor Francen was a Belgian-born French actor known for his distinguished presence in European and Hollywood films of the 1930s and 1940s.
  • 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_69b3453d91548190b4d4ef8fe52aa2ac completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b34e8a676c8190ac2cb59e62613dd9 completed March 12, 2026, 11:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5b779a93081909af1abdf664f040f completed March 14, 2026, 7:31 p.m.
Created at: March 12, 2026, 11:05 p.m.