Triple

T6500837
Position Surface form Disambiguated ID Type / Status
Subject Marita E148881 entity
Predicate hasVariant P455 FINISHED
Object Maritta
Maritta is a feminine given name, typically considered a variant of names like Marita or Maria used in various European cultures.
 E600485 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: Maritta | Statement: [Marita, hasVariant, Maritta]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Maritta
Context triple: [Marita, hasVariant, Maritta]
  • A. Ranna
    Ranna was a prominent 10th-century Kannada poet, celebrated as one of the “three gems” of early Kannada literature for his influential epic and courtly works.
  • B. Ema
    Ema is a given name used as a variant spelling of Emma in various languages and cultures.
  • C. Maiana
    Maiana is a low-lying coral atoll in the central Pacific nation of Kiribati, known for its traditional village life and vulnerability to sea-level rise.
  • D. Moura
    Moura is a historic town in Portugal’s Alentejo region, known for its whitewashed architecture, olive oil production, and proximity to the Alqueva reservoir.
  • E. Moura
    Moura is a small coal-mining town in Central Queensland, Australia, known for its agricultural activities and history of mining disasters.
  • 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: Maritta
Triple: [Marita, hasVariant, Maritta]
Generated description
Maritta is a feminine given name, typically considered a variant of names like Marita or Maria used in various European cultures.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Maritta
Target entity description: Maritta is a feminine given name, typically considered a variant of names like Marita or Maria used in various European cultures.
  • A. Ranna
    Ranna was a prominent 10th-century Kannada poet, celebrated as one of the “three gems” of early Kannada literature for his influential epic and courtly works.
  • B. Ema
    Ema is a given name used as a variant spelling of Emma in various languages and cultures.
  • C. Maiana
    Maiana is a low-lying coral atoll in the central Pacific nation of Kiribati, known for its traditional village life and vulnerability to sea-level rise.
  • D. Moura
    Moura is a historic town in Portugal’s Alentejo region, known for its whitewashed architecture, olive oil production, and proximity to the Alqueva reservoir.
  • E. Moura
    Moura is a small coal-mining town in Central Queensland, Australia, known for its agricultural activities and history of mining disasters.
  • 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_69c687e9ad288190bae5bcac9c8ac855 completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c68ad2e148819088be5c48ad73dc59 completed March 27, 2026, 1:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6cb26d2d08190a52084c3a8c0d8f8 completed March 27, 2026, 6:23 p.m.
NEDg Description generation batch_69c6cd03c56c8190a0e7c69597ab8c83 completed March 27, 2026, 6:31 p.m.
NED2 Entity disambiguation (via description) batch_69c6cdfc23988190a4062abbcc312cb4 completed March 27, 2026, 6:35 p.m.
Created at: March 27, 2026, 1:42 p.m.