Triple

T788105
Position Surface form Disambiguated ID Type / Status
Subject P. Diddy E16848 entity
Predicate hasChild P369 FINISHED
Object D'Lila Star Combs
D'Lila Star Combs is one of Sean "Diddy" Combs' twin daughters, known publicly through her association with the music mogul and occasional appearances in media and fashion events.
 E98773 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: D'Lila Star Combs | Statement: [P. Diddy, hasChild, D'Lila Star Combs]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: D'Lila Star Combs
Context triple: [P. Diddy, hasChild, D'Lila Star Combs]
  • A. Lilly Belle
    Lilly Belle is a steam locomotive that operates on the Walt Disney World Railroad at the Magic Kingdom theme park in Florida.
  • B. Charlene
    Charlene is a feminine given name derived from the male name Charles.
  • C. Roberta
    Roberta is a feminine given name commonly used in various languages, derived from the masculine name Robert.
  • D. Zella
    Zella is an activewear and athleisure clothing brand known for its performance-focused yet stylish designs, sold at Nordstrom.
  • E. Nance
    Nance is the middle name of John Nance Garner, the 32nd vice president of the United States under Franklin D. Roosevelt.
  • 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: D'Lila Star Combs
Triple: [P. Diddy, hasChild, D'Lila Star Combs]
Generated description
D'Lila Star Combs is one of Sean "Diddy" Combs' twin daughters, known publicly through her association with the music mogul and occasional appearances in media and fashion events.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: D'Lila Star Combs
Target entity description: D'Lila Star Combs is one of Sean "Diddy" Combs' twin daughters, known publicly through her association with the music mogul and occasional appearances in media and fashion events.
  • A. Lilly Belle
    Lilly Belle is a steam locomotive that operates on the Walt Disney World Railroad at the Magic Kingdom theme park in Florida.
  • B. Charlene
    Charlene is a feminine given name derived from the male name Charles.
  • C. Roberta
    Roberta is a feminine given name commonly used in various languages, derived from the masculine name Robert.
  • D. Zella
    Zella is an activewear and athleisure clothing brand known for its performance-focused yet stylish designs, sold at Nordstrom.
  • E. Nance
    Nance is the middle name of John Nance Garner, the 32nd vice president of the United States under Franklin D. Roosevelt.
  • 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_69a4936cb7448190914f5fe4b8d81607 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4a782fe988190966b958673fe12bf completed March 1, 2026, 8:54 p.m.
NED1 Entity disambiguation (via context triple) batch_69a79286e8b88190887def813bc65d95 completed March 4, 2026, 2:01 a.m.
NEDg Description generation batch_69a792edde248190859bbef2b50c39a0 completed March 4, 2026, 2:03 a.m.
NED2 Entity disambiguation (via description) batch_69a79342d4108190831131e85f2886c8 completed March 4, 2026, 2:04 a.m.
Created at: March 1, 2026, 7:38 p.m.