Triple

T9069042
Position Surface form Disambiguated ID Type / Status
Subject Tonight E217314 entity
Predicate performedByCharacter P14884 FINISHED
Object Maria (character)
Maria is the optimistic, music-loving novice-turned-governess and eventual wife of Captain von Trapp in the classic musical and film "The Sound of Music."
 E776068 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: Maria (character) | Statement: [Tonight, performedByCharacter, Maria (character)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Maria (character)
Context triple: [Tonight, performedByCharacter, Maria (character)]
  • A. Marian
    Marian is a given name of Latin origin commonly used in various European countries for both males and females.
  • B. Marian
    Marian is a small rural town and sugar-growing community in Queensland, Australia, located within the Mackay Region.
  • C. Marisa
    Marisa is a feminine given name of Latin origin, commonly used in Spanish- and Italian-speaking cultures.
  • D. Marsha
    Marsha is a feminine given name commonly used in English-speaking countries, often considered a variant of the name Marcia.
  • E. Joanna
    Joanna is a feminine given name used in various cultures, often associated with forms of the name John and shared by many notable historical and contemporary figures.
  • 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: Maria (character)
Triple: [Tonight, performedByCharacter, Maria (character)]
Generated description
Maria is the optimistic, music-loving novice-turned-governess and eventual wife of Captain von Trapp in the classic musical and film "The Sound of Music."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Maria (character)
Target entity description: Maria is the optimistic, music-loving novice-turned-governess and eventual wife of Captain von Trapp in the classic musical and film "The Sound of Music."
  • A. Marian
    Marian is a given name of Latin origin commonly used in various European countries for both males and females.
  • B. Marian
    Marian is a small rural town and sugar-growing community in Queensland, Australia, located within the Mackay Region.
  • C. Marisa
    Marisa is a feminine given name of Latin origin, commonly used in Spanish- and Italian-speaking cultures.
  • D. Marsha
    Marsha is a feminine given name commonly used in English-speaking countries, often considered a variant of the name Marcia.
  • E. Joanna
    Joanna is a feminine given name used in various cultures, often associated with forms of the name John and shared by many notable historical and contemporary figures.
  • 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_69ca83d5a7f48190b16c1e59bd43ede0 completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69cc955ba250819085fa49e0059d06c1 completed April 1, 2026, 3:47 a.m.
NED1 Entity disambiguation (via context triple) batch_69cffde470388190ae88a96654404410 completed April 3, 2026, 5:50 p.m.
NEDg Description generation batch_69d000d2c5688190b014ce33c04ff875 completed April 3, 2026, 6:02 p.m.
NED2 Entity disambiguation (via description) batch_69d001a1056c819083793547dbd4b1ee completed April 3, 2026, 6:06 p.m.
Created at: March 30, 2026, 7:11 p.m.