Triple

T604291
Position Surface form Disambiguated ID Type / Status
Subject Hans Bethe E11562 entity
Predicate givenName P17 FINISHED
Object Hans E75878 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: Hans | Statement: [Hans Bethe, givenName, Hans]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hans
Context triple: [Hans Bethe, givenName, Hans]
  • A. Hans chosen
    Hans is a masculine given name of Germanic origin commonly used in Germanic and Scandinavian countries.
  • B. Helmut
    Helmut is a masculine given name of German origin, historically common in German-speaking countries.
  • C. Oskar
    Oskar is a masculine given name of Germanic origin, commonly used in various European countries.
  • D. Karl
    Karl Schwarzschild was a German physicist and astronomer best known for providing the first exact solution to Einstein’s field equations, leading to the concept of the Schwarzschild black hole.
  • E. Karl
    Karl is the given first name of Charles Proteus Steinmetz, the renowned German-American mathematician and electrical engineer who revolutionized the understanding of alternating current systems.
  • 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_69a4932779b881908688590d59c71900 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a49dc67b248190b0bb195553f03be8 completed March 1, 2026, 8:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69a5c389eb708190911de8a28e55ab7f completed March 2, 2026, 5:06 p.m.
Created at: March 1, 2026, 7:35 p.m.