Triple

T4488975
Position Surface form Disambiguated ID Type / Status
Subject Gregor Strasser E107320 entity
Predicate givenName P17 FINISHED
Object Gregor E194828 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: Gregor | Statement: [Gregor Strasser, givenName, Gregor]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gregor
Context triple: [Gregor Strasser, givenName, Gregor]
  • A. Gregor chosen
    Gregor is a masculine given name of Latin origin, commonly associated with figures such as the pioneering geneticist Gregor Mendel.
  • B. Gregor Samsa
    Gregor Samsa is the beleaguered traveling salesman who famously awakens transformed into a giant insect in Franz Kafka’s novella "The Metamorphosis."
  • C. Anton
    Anton is a masculine given name of Latin origin, commonly used in various European and Slavic countries.
  • D. Alois
    Alois is a masculine given name of Germanic origin, notably borne by Alois Hitler, the father of Adolf Hitler.
  • E. Sigmund
    Sigmund is the given name of Sigmund Freud, the pioneering Austrian neurologist and founder of psychoanalysis.
  • 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_69bd43f84f788190a1383579c4a595be completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd52ad36748190b791de458f2116b2 completed March 20, 2026, 1:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69bd67a90f308190ab4f912cd1e2f692 completed March 20, 2026, 3:28 p.m.
Created at: March 20, 2026, 12:59 p.m.