Triple

T13210816
Position Surface form Disambiguated ID Type / Status
Subject Xscape E314484 entity
Predicate formerMember P1168 FINISHED
Object Tamika Scott E1036886 NE FINISHED

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: Tamika Scott | Statement: [Xscape, formerMember, Tamika Scott]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tamika Scott
Context triple: [Xscape, formerMember, Tamika Scott]
  • A. Tamika Scott chosen
    Tamika Scott is an American R&B singer and songwriter best known as a member of the multi-platinum 1990s girl group Xscape.
  • B. Tyisha Bogues
    Tyisha Bogues is the daughter of former NBA point guard Muggsy Bogues.
  • C. Courtney Hodges
    Courtney Hodges was a senior U.S. Army general in World War II who led First Army in Western Europe, playing a key role in the Allied advance from Normandy into Germany.
  • D. LaTisha Scott
    LaTisha Scott is a reality television personality and real estate entrepreneur best known for appearing on the OWN series "Love & Marriage: Huntsville."
  • E. Tyasha Harris
    Tyasha Harris is an American professional basketball player and standout point guard who starred for the University of South Carolina Gamecocks women’s basketball program.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69d806aee7308190b70a237ba2a6e3e1 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d98c9e072c8190b66e2c2430628ed0 completed April 10, 2026, 11:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7546b9ae081909f97fc4a06b8f927 completed May 3, 2026, 1:58 p.m.
Created at: April 9, 2026, 9:17 p.m.