Triple

T23529883
Position Surface form Disambiguated ID Type / Status
Subject There's Always Tomorrow E576533 entity
Predicate author P4 FINISHED
Object Elizabeth Young
Elizabeth Young is a British author best known for her contemporary romantic comedies, including the novel that inspired the film "The Wedding Date."
 E1592302 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: Elizabeth Young | Statement: [There's Always Tomorrow, author, Elizabeth Young]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Elizabeth Young
Context triple: [There's Always Tomorrow, author, Elizabeth Young]
  • A. Elizabeth Young
    Elizabeth Young was an American actress active in the 1930s who appeared in several Hollywood films before retiring from the screen.
  • B. Elizabeth Young
    Elizabeth Young is a writer best known for her novel "East of Java."
  • C. Freya Ridings
    Freya Ridings is an English singer-songwriter and pianist known for her emotive vocals and breakout hit single "Lost Without You."
  • D. Faye Marsay
    Faye Marsay is an English actress known for her roles in film and television, including appearances in "Game of Thrones," "Black Mirror," and "Pride."
  • E. Lady Wray
    Lady Wray is the stage name of American R&B and soul singer Nicole Wray, known for her powerful vocals and retro-inspired sound.
  • 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: Elizabeth Young
Triple: [There's Always Tomorrow, author, Elizabeth Young]
Generated description
Elizabeth Young is a British author best known for her contemporary romantic comedies, including the novel that inspired the film "The Wedding Date."

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_69e245f5a8848190a2ba42e271c6c31f completed April 17, 2026, 2:38 p.m.
NER Named-entity recognition batch_69f1ac7646a48190b5dcbaf8c0c194df completed April 29, 2026, 7 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0cdf53c66c819087f1e9481dcfc8ee completed May 19, 2026, 10:08 p.m.
NEDg Description generation batch_6a0ce4602a408190b4357d98cf16477a completed May 19, 2026, 10:29 p.m.
NED2 Entity disambiguation (via description) batch_6a0d721bdae08190a06f48a6073c5351 completed May 20, 2026, 8:34 a.m.
Created at: April 17, 2026, 6:09 p.m.