Triple

T10348471
Position Surface form Disambiguated ID Type / Status
Subject Marta E243815 entity
Predicate relatedName P3889 FINISHED
Object Marta (Spanish form) E241291 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: Marta (Spanish form) | Statement: [Marta, relatedName, Marta (Spanish form)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Marta (Spanish form)
Context triple: [Marta, relatedName, Marta (Spanish form)]
  • A. Marta (Spanish) chosen
    Marta is the Spanish given name equivalent to Martha, commonly used in Spanish-speaking countries.
  • B. Marta (Polish)
    Marta is a common Polish female given name, equivalent to Martha, traditionally associated with Christian and European naming traditions.
  • C. Marta (Scandinavian languages)
    Marta is the Scandinavian form of the female given name Martha, commonly used in countries such as Sweden, Norway, and Denmark.
  • D. Marta
    Marta is a feminine given name commonly used in many European and Latin American countries, often considered a variant of the name Martha.
  • E. Marta
    Marta is a small Italian town in the Lazio region, situated on the southern shore of Lake Bolsena and known for its lakeside scenery and historic center.
  • 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_69d381b22b8c8190aaed476be5f872a9 completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4e945d51881908dd2af6c78344c9b completed April 7, 2026, 11:23 a.m.
NED1 Entity disambiguation (via context triple) batch_69d7508e325c8190a88c2b972f8a6846 completed April 9, 2026, 7:09 a.m.
Created at: April 6, 2026, 11:56 a.m.