Triple

T15026889
Position Surface form Disambiguated ID Type / Status
Subject Atari 7800 E378239 entity
Predicate codename P2980 FINISHED
Object Maria
Maria is the custom graphics chip used in the Atari 7800 video game console, responsible for handling its advanced 2D visuals.
E1135798 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 | Statement: [Atari 7800, codename, Maria]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Maria
Context triple: [Atari 7800, codename, Maria]
  • A. Maria
    Maria is an Italian woman best known as the younger sister of actress Sophia Loren and the former wife of film producer Romano Mussolini.
  • B. Maria
    Maria is a character in the period drama film "Stage Beauty," which explores gender roles and the world of 17th-century English theatre.
  • C. Maria
    Maria is a track on Rage Against the Machine’s 2000 album "The Battle of Los Angeles," known for its politically charged lyrics and aggressive rap metal sound.
  • D. Maria
    Maria I of Portugal was the first queen regnant of Portugal, known for her devout Catholicism, initial period of enlightened reforms, and later mental illness that led to her son acting as regent.
  • E. Maria
    Maria is a witty and sharp-tongued lady-in-waiting to the Princess of France in William Shakespeare’s comedy "Love's Labour's Lost."
  • 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
Triple: [Atari 7800, codename, Maria]
Generated description
Maria is the custom graphics chip used in the Atari 7800 video game console, responsible for handling its advanced 2D visuals.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Maria
Target entity description: Maria is the custom graphics chip used in the Atari 7800 video game console, responsible for handling its advanced 2D visuals.
  • A. Maria
    Maria is a friendly human character from Sesame Street known for her warm personality and close relationships with the show's Muppet residents.
  • B. Maria
    Maria is a powerful and ruthless vampire from the Twilight series, known for creating and commanding a newborn vampire army in the American South.
  • C. Maria
    Maria was a Byzantine empress consort and the mother of Emperor Constantine V in the 8th-century Byzantine Empire.
  • D. Maria
    Maria was a Byzantine empress consort, known primarily as the wife of Emperor Constantine V in the 8th-century Byzantine Empire.
  • E. Maria
    Maria is a woman known primarily as the daughter of Theophilus.
  • 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_69d85cd46b2c819090d054c27787f677 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69ded7dfcb508190aec8cd667e27a8ea completed April 15, 2026, 12:12 a.m.
NED1 Entity disambiguation (via context triple) batch_69fea5b0bbf4819082e14715bfd6003d completed May 9, 2026, 3:10 a.m.
NEDg Description generation batch_69fea6f926d481908cf4465205c628db completed May 9, 2026, 3:16 a.m.
NED2 Entity disambiguation (via description) batch_69fea9ab97e08190995c090c1fb9ed3b completed May 9, 2026, 3:27 a.m.
Created at: April 10, 2026, 2:58 a.m.