Triple

T39031
Position Surface form Disambiguated ID Type / Status
Subject William E772 entity
Predicate cognate P2527 FINISHED
Object Guglielmo E6688 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: Guglielmo | Statement: [William, cognate, Guglielmo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Guglielmo
Context triple: [William, cognate, Guglielmo]
  • A. Andreas
    Andreas is a masculine given name of Greek origin, commonly used in various European and international cultures.
  • B. King of Italy
    The King of Italy was a monarchical title used in various historical periods to designate the sovereign ruler of the Italian kingdom, most notably during the Napoleonic era and later the unified Kingdom of Italy.
  • C. Theodor
    Theodor "Ted" Nelson is an American pioneer of information technology best known for coining the term "hypertext" and envisioning global hyperlinked document systems.
  • D. Willem chosen
    Willem is a given name, primarily used in Dutch-speaking regions, that corresponds to the English name William.
  • E. António
    António is a common Portuguese given name, notably borne by António Guterres, the Secretary-General of the United Nations.
  • 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_69a247a8f6c08190bac804906d62ed5a completed Feb. 28, 2026, 1:40 a.m.
NER Named-entity recognition batch_69a24ec1ef5481909daf99654dfa3f57 completed Feb. 28, 2026, 2:11 a.m.
NED1 Entity disambiguation (via context triple) batch_69a26c15db808190b8d66206a4ed1085 completed Feb. 28, 2026, 4:16 a.m.
Created at: Feb. 28, 2026, 1:46 a.m.