Triple

T3512101
Position Surface form Disambiguated ID Type / Status
Subject Leopold Joseph von Daun E74219 entity
Predicate givenName P17 FINISHED
Object Leopold E110183 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: Leopold | Statement: [Leopold Joseph von Daun, givenName, Leopold]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Leopold
Context triple: [Leopold Joseph von Daun, givenName, Leopold]
  • A. Leopold chosen
    Leopold is a masculine given name of Germanic origin historically borne by various European rulers, saints, and notable figures.
  • B. Ludwik
    Ludwik is a given name, primarily used in Polish, that corresponds to the name Ludwig in other European languages.
  • C. Ernst
    Ernst is a masculine given name of Germanic origin, commonly used in German-speaking and Scandinavian countries.
  • D. Günther
    Günther is a German masculine given name traditionally associated with figures of Germanic origin and culture.
  • E. Theodor
    Theodor "Ted" Nelson is an American pioneer of information technology best known for coining the term "hypertext" and envisioning global hyperlinked document 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_69ad85cfb5c881909c9a2edd9d6043cc completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adbc10b6b48190bedfed6d34afc425 completed March 8, 2026, 6:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69b37e7366e4819099b4a411343bdd90 completed March 13, 2026, 3:03 a.m.
Created at: March 8, 2026, 3:19 p.m.