Triple

T5073434
Position Surface form Disambiguated ID Type / Status
Subject Marta Navarro E114334 entity
Predicate hasNameComponentOrigin P31098 FINISHED
Object Marta is of Hebrew origin 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 is of Hebrew origin | Statement: [Marta Navarro, hasNameComponentOrigin, Marta is of Hebrew origin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Marta is of Hebrew origin
Context triple: [Marta Navarro, hasNameComponentOrigin, Marta is of Hebrew origin]
  • A. Maria is of Hebrew origin
    Maria Paola is a feminine given name that combines the widely used, Hebrew-derived name Maria with the Italian form of Paul, Paola.
  • B. Marta (Spanish) chosen
    Marta is the Spanish given name equivalent to Martha, commonly used in Spanish-speaking countries.
  • C. Marta (Polish)
    Marta is a common Polish female given name, equivalent to Martha, traditionally associated with Christian and European naming traditions.
  • D. Marta (Scandinavian languages)
    Marta is the Scandinavian form of the female given name Martha, commonly used in countries such as Sweden, Norway, and Denmark.
  • E. Marta (Czech)
    Marta is the Czech form of the female given name Martha, commonly used in Czech-speaking countries.
  • 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_69bd443cf28c8190ad371d603563dbdd completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd74cfa4348190bc50590117a6bcf9 completed March 20, 2026, 4:24 p.m.
NED1 Entity disambiguation (via context triple) batch_69beb11600ac81908661759839ebfc98 completed March 21, 2026, 2:54 p.m.
Created at: March 20, 2026, 1:39 p.m.