Triple

T2179924
Position Surface form Disambiguated ID Type / Status
Subject Martha E49016 entity
Predicate hasVariant P455 FINISHED
Object Marta
Marta is a feminine given name commonly used in many European and Latin American countries, often considered a variant of the name Martha.
 E243815 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: Marta | Statement: [Martha, hasVariant, Marta]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Marta
Context triple: [Martha, hasVariant, Marta]
  • 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. Paola
    Paola is an Italian noblewoman who became Queen consort of Belgium as the wife of King Albert II.
  • D. Magda
    Magda is a feminine given name, commonly used as a short form of Magdalena in various European languages.
  • E. Renata
    Renata is a young Venetian woman who becomes the poignant love interest of an aging American colonel in Ernest Hemingway’s novel "Across the River and Into the Trees."
  • 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: Marta
Triple: [Martha, hasVariant, Marta]
Generated description
Marta is a feminine given name commonly used in many European and Latin American countries, often considered a variant of the name Martha.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Marta
Target entity description: Marta is a feminine given name commonly used in many European and Latin American countries, often considered a variant of the name Martha.
  • 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. Paola
    Paola is an Italian noblewoman who became Queen consort of Belgium as the wife of King Albert II.
  • D. Magda
    Magda is a feminine given name, commonly used as a short form of Magdalena in various European languages.
  • E. Renata
    Renata is a young Venetian woman who becomes the poignant love interest of an aging American colonel in Ernest Hemingway’s novel "Across the River and Into the Trees."
  • 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_69a88aa72d348190a9544bb5b8a4e71d completed March 4, 2026, 7:40 p.m.
NER Named-entity recognition batch_69abbef0e2f0819080ca457fe3b8b419 completed March 7, 2026, 6 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae653de18481909c3521e060540a38 completed March 9, 2026, 6:14 a.m.
NEDg Description generation batch_69ae65d419048190ad723d21ab7f1cab completed March 9, 2026, 6:16 a.m.
NED2 Entity disambiguation (via description) batch_69ae666e71908190b50be2cac5bdfa28 completed March 9, 2026, 6:19 a.m.
Created at: March 4, 2026, 7:45 p.m.