Triple

T3718099
Position Surface form Disambiguated ID Type / Status
Subject Jewish American literature E81577 entity
Predicate hasNotableWork P4 FINISHED
Object Herzog E161955 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: Herzog | Statement: [Jewish American literature, hasNotableWork, Herzog]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Herzog
Context triple: [Jewish American literature, hasNotableWork, Herzog]
  • A. Herzog chosen
    Herzog is a German surname borne by numerous notable figures in politics, arts, and academia, and is also the title of a celebrated novel by Saul Bellow.
  • B. Günther
    Günther is a German masculine given name traditionally associated with figures of Germanic origin and culture.
  • C. Ernst
    Ernst is a masculine given name of Germanic origin, commonly used in German-speaking and Scandinavian countries.
  • D. Leopold
    Leopold is a masculine given name of Germanic origin historically borne by various European rulers, saints, and notable figures.
  • E. Modrow
    Modrow is a German surname most notably associated with Hans Modrow, the last communist premier of East Germany.
  • 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_69ad8b1a81588190b3f27a5483bb610e completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69adca984844819087a2f6b20d2f19e7 completed March 8, 2026, 7:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4ce1260948190b4707337e9427c2c completed March 14, 2026, 2:55 a.m.
Created at: March 8, 2026, 3:33 p.m.