Triple

T26385778
Position Surface form Disambiguated ID Type / Status
Subject If/Then E663274 entity
Predicate starredOriginalBroadwayCast P4737 FINISHED
Object Tamika Lawrence
Tamika Lawrence is an American stage and screen actress and singer known for her powerful vocals and performances in Broadway productions and musical theatre.
 E1720803 NE FINISHED

How this triple was built (3 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 Lawrence | Statement: [If/Then, starredOriginalBroadwayCast, Tamika Lawrence]
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: Tamika Lawrence
Triple: [If/Then, starredOriginalBroadwayCast, Tamika Lawrence]
Generated description
Tamika Lawrence is an American stage and screen actress and singer known for her powerful vocals and performances in Broadway productions and musical theatre.
PD Predicate disambiguation gpt-5-mini-2025-08-07 
Target predicate: starredOriginalBroadwayCast
Context triple: [If/Then, starredOriginalBroadwayCast, Tamika Lawrence]
  • A. originalBroadwayStar chosen
    Indicates that the subject was a member of the original Broadway cast in the specified role or production.
  • B. originalBroadwayProductionTheatre
    Indicates the theatre venue where a work’s original Broadway production was staged.
  • C. appearedInBroadwayProduction
    Indicates that an entity participated as part of a Broadway stage production of another work or show.
  • D. broadwayOriginalLanguage
    Indicates the original language in which a Broadway production was first written or performed.
  • E. originalBroadwayCoStar
    Indicates that two performers appeared together as co-stars in the original Broadway production of the same show.
  • F. None of above.

Provenance (6 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_69ee88374adc81909868f3bab374a32f completed April 26, 2026, 9:48 p.m.
NER Named-entity recognition batch_69f6247480cc8190a887eedaeb94615c completed May 2, 2026, 4:21 p.m.
NED1 Entity disambiguation (via context triple) batch_6a119a7cabbc8190a445f6fa865c2446 completed May 23, 2026, 12:15 p.m.
NEDg Description generation batch_6a119b15cbb4819087ea26f6c87d8732 completed May 23, 2026, 12:18 p.m.
NED2 Entity disambiguation (via description) batch_6a119bad614481909156c765ce266350 completed May 23, 2026, 12:21 p.m.
PD Predicate disambiguation batch_69f623a7539c8190b71797f583da9f63 completed May 2, 2026, 4:17 p.m.
Created at: April 26, 2026, 11:22 p.m.