Triple

T8113718
Position Surface form Disambiguated ID Type / Status
Subject Marissa Ribisi E189418 entity
Predicate givenName P17 FINISHED
Object Marissa
Marissa is a feminine given name commonly used in English-speaking countries.
 E713511 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: Marissa | Statement: [Marissa Ribisi, givenName, Marissa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Marissa
Context triple: [Marissa Ribisi, givenName, Marissa]
  • A. Sheilia
    Sheilia is a feminine given name, typically considered an alternative spelling of the name Sheila.
  • B. Marisa
    Marisa is a feminine given name of Latin origin, commonly used in Spanish- and Italian-speaking cultures.
  • C. Marla
    Marla is a feminine given name most notably borne by American actress and television personality Marla Maples.
  • D. Katisha
    Katisha is a formidable, older noblewoman and comic villainess in Gilbert and Sullivan’s operetta "The Mikado," known for her dramatic presence and unrequited love for Nanki-Poo.
  • E. Shira
    Shira is the eroded western volcanic cone and plateau of Mount Kilimanjaro, forming one of the mountain’s three main summits.
  • 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: Marissa
Triple: [Marissa Ribisi, givenName, Marissa]
Generated description
Marissa is a feminine given name commonly used in English-speaking countries.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Marissa
Target entity description: Marissa is a feminine given name commonly used in English-speaking countries.
  • A. Sheilia
    Sheilia is a feminine given name, typically considered an alternative spelling of the name Sheila.
  • B. Marisa
    Marisa is a feminine given name of Latin origin, commonly used in Spanish- and Italian-speaking cultures.
  • C. Marla
    Marla is a feminine given name most notably borne by American actress and television personality Marla Maples.
  • D. Katisha
    Katisha is a formidable, older noblewoman and comic villainess in Gilbert and Sullivan’s operetta "The Mikado," known for her dramatic presence and unrequited love for Nanki-Poo.
  • E. Shira
    Shira is the eroded western volcanic cone and plateau of Mount Kilimanjaro, forming one of the mountain’s three main summits.
  • 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_69ca82baad008190ab2859712b9b1607 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb432f2a24819097be6ab9b03567bd completed March 31, 2026, 3:44 a.m.
NED1 Entity disambiguation (via context triple) batch_69cc943bdaa48190971bf57ae4fb5c21 completed April 1, 2026, 3:42 a.m.
NEDg Description generation batch_69cc9557c6148190a759021b6add0a61 completed April 1, 2026, 3:47 a.m.
NED2 Entity disambiguation (via description) batch_69cc96a8bb688190a352de1798b380f1 completed April 1, 2026, 3:53 a.m.
Created at: March 30, 2026, 5:32 p.m.