Triple

T23557639
Position Surface form Disambiguated ID Type / Status
Subject Borderline E579129 entity
Predicate includesTrack P3284 FINISHED
Object My Maria NE NERFINISHED

How this triple was built (2 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: My Maria | Statement: [Borderline, includesTrack, My Maria]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: My Maria
Context triple: [Borderline, includesTrack, My Maria]
  • A. My Maria chosen
    "My Maria" is a popular country song, originally recorded by B.W. Stevenson and later made famous by the American country duo Brooks & Dunn with their hit 1996 cover.
  • B. Mamacita
    "Mamacita" is a popular hip-hop track by Travis Scott featuring Rich Homie Quan and Young Thug, known for its moody production and melodic trap style.
  • C. Mamacita
    "Mamacita" is a popular reggae/dancehall track by Bermudian artist Collie Buddz known for its catchy, laid-back Caribbean vibe.
  • D. Carmen
    Carmen is a pivotal character in the 1986 film "The Color of Money," serving as the savvy and manipulative girlfriend-manager of young pool hustler Vincent Lauria.
  • E. Carmen
    Carmen is the central protagonist of the story "Abracadabra," around whom the plot and character dynamics revolve.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e245fe24588190888f3aec8407d8e3 completed April 17, 2026, 2:38 p.m.
NER Named-entity recognition batch_69f1af659e9881908b527accfd2b1187 completed April 29, 2026, 7:12 a.m.
Created at: April 17, 2026, 6:12 p.m.