Triple

T17023387
Position Surface form Disambiguated ID Type / Status
Subject Debbi Morgan E413001 entity
Predicate notableWork P4 FINISHED
Object Love & Basketball E161178 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: Love & Basketball | Statement: [Debbi Morgan, notableWork, Love & Basketball]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Love & Basketball
Context triple: [Debbi Morgan, notableWork, Love & Basketball]
  • A. Love & Basketball chosen
    Love & Basketball is a 2000 romantic drama film that follows two childhood friends whose shared passion for basketball intertwines with their evolving love story over the years.
  • B. Basketball: A Love Story
    Basketball: A Love Story is a comprehensive documentary and oral history project that explores the evolution, culture, and iconic figures of basketball through a wide range of interviews and stories.
  • C. Hoops
    Hoops is a television series associated with producer and manager Michael Rotenberg.
  • D. Hoops
    Hoops is a basketball-inspired game mode in Rocket League where players score by shooting the ball into elevated hoops instead of traditional soccer goals.
  • E. Dear Basketball
    Dear Basketball is an Academy Award–winning animated short film based on Kobe Bryant’s poetic farewell to the sport.
  • 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_69d886cc4170819093deddc7b8b4b6a7 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3d5d2abbc81908943becf5f539fc6 completed April 18, 2026, 7:04 p.m.
NED1 Entity disambiguation (via context triple) batch_6a011b514de481909c78c17a3014b468 completed May 10, 2026, 11:57 p.m.
Created at: April 10, 2026, 5:33 a.m.