Triple

T2269610
Position Surface form Disambiguated ID Type / Status
Subject Gregory E50625 entity
Predicate hasFeminineForm P1613 FINISHED
Object Gregoria
Gregoria is a feminine given name derived from the masculine name Gregory, commonly used in various European languages.
 E251636 NE FINISHED

How this triple was built (4 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: [Gregory, hasFeminineForm, Gregoria]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Gregoria
Context triple: [Gregory, hasFeminineForm, Gregoria]
  • A. María
    "María" is a film featuring actress Taryn Power in a significant role.
  • B. María
    María is a key character in Ernest Hemingway's novel "For Whom the Bell Tolls," known as a young Spanish woman and love interest of the protagonist amid the Spanish Civil War.
  • C. Josefa
    Josefa is a feminine given name of Spanish origin, historically borne by notable figures such as Mexican independence heroine Josefa Ortiz de Domínguez.
  • D. Luciana
    Luciana is a feminine given name of Latin origin, commonly used in Spanish- and Portuguese-speaking countries.
  • E. Paola
    Paola is an Italian noblewoman who became Queen consort of Belgium as the wife of King Albert II.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Gregoria
Triple: [Gregory, hasFeminineForm, Gregoria]
Generated description
Gregoria is a feminine given name derived from the masculine name Gregory, commonly used in various European languages.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Gregoria
Target entity description: Gregoria is a feminine given name derived from the masculine name Gregory, commonly used in various European languages.
  • A. María
    María is a key character in Ernest Hemingway's novel "For Whom the Bell Tolls," known as a young Spanish woman and love interest of the protagonist amid the Spanish Civil War.
  • B. María
    "María" is a film featuring actress Taryn Power in a significant role.
  • C. Josefa
    Josefa is a feminine given name of Spanish origin, historically borne by notable figures such as Mexican independence heroine Josefa Ortiz de Domínguez.
  • D. Luciana
    Luciana is a feminine given name of Latin origin, commonly used in Spanish- and Portuguese-speaking countries.
  • E. Paola
    Paola is an Italian noblewoman who became Queen consort of Belgium as the wife of King Albert II.
  • F. None of above. chosen

Provenance (5 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_69a88b05910c8190a9a2b1ff230c85f9 completed March 4, 2026, 7:41 p.m.
NER Named-entity recognition batch_69abc1bd376c8190a43decde599f62e6 completed March 7, 2026, 6:12 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae71d97a108190a26ffd20fac91a7e completed March 9, 2026, 7:08 a.m.
NEDg Description generation batch_69ae73a4bdd08190bb9fff64ffdbeed6 completed March 9, 2026, 7:15 a.m.
NED2 Entity disambiguation (via description) batch_69ae776fdfb48190ae8731002c537458 completed March 9, 2026, 7:32 a.m.
Created at: March 4, 2026, 7:48 p.m.