Triple

T1963539
Position Surface form Disambiguated ID Type / Status
Subject Benedict E42638 entity
Predicate hasFeminineForm P1613 FINISHED
Object Benedicta E192548 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: Benedicta | Statement: [Benedict, hasFeminineForm, Benedicta]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Benedicta
Context triple: [Benedict, hasFeminineForm, Benedicta]
  • A. Margareta
    Margareta is a feminine given name used in various European languages, closely related to and derived from the name Margaret.
  • B. Benedetta chosen
    Benedetta is an Italian feminine given name, equivalent to "Benedicta" and commonly used in Italy and other Italian-speaking communities.
  • C. Hildegard
    Hildegard is a Germanic female given name, historically borne by several notable medieval figures, most famously the mystic and polymath Hildegard of Bingen.
  • D. Winifred
    Winifred is the given name of Winnie Madikizela-Mandela, the prominent South African anti-apartheid activist and politician.
  • E. Ricarda
    Ricarda is a feminine given name, primarily used in German- and Spanish-speaking countries, derived from the male name Richard.
  • 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_69a88711151c8190940b2572095059d7 completed March 4, 2026, 7:25 p.m.
NER Named-entity recognition batch_69abb3ac31a08190abaecac8badc52c7 completed March 7, 2026, 5:12 a.m.
NED1 Entity disambiguation (via context triple) batch_69adfbd32eb88190a2069b6490b12e5d completed March 8, 2026, 10:44 p.m.
Created at: March 4, 2026, 7:36 p.m.