Triple

T8320868
Position Surface form Disambiguated ID Type / Status
Subject Gregor E194828 entity
Predicate hasFeminineForm P1613 FINISHED
Object Gregoria E251636 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: Gregoria | Statement: [Gregor, hasFeminineForm, Gregoria]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gregoria
Context triple: [Gregor, hasFeminineForm, Gregoria]
  • A. Gregoria chosen
    Gregoria is a feminine given name derived from the masculine name Gregory, commonly used in various European languages.
  • B. María
    "María" is a film featuring actress Taryn Power in a significant role.
  • C. María
    María is a feminine given name of Hebrew origin, widely used in Spanish-speaking countries and associated with numerous historical and religious figures.
  • D. María
    "María" is a 1995 Latin pop hit by Puerto Rican singer Ricky Martin that became one of his signature international breakthrough songs.
  • E. María
    María is the given first name of Josefa Ortiz de Domínguez, a prominent figure in Mexico’s War of Independence.
  • 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_69ca82e7a8a88190a32bb5cc0feb012d completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb7f67aee88190b245f8d6e57a40b2 completed March 31, 2026, 8:01 a.m.
NED1 Entity disambiguation (via context triple) batch_69cd95a058948190b056d9b0f0607933 completed April 1, 2026, 10:01 p.m.
Created at: March 30, 2026, 5:55 p.m.