Triple

T995501
Position Surface form Disambiguated ID Type / Status
Subject Jules Laforgue E21485 entity
Predicate spouse P13 FINISHED
Object Leah Lee
Leah Lee was the wife of French Symbolist poet Jules Laforgue, known primarily through her association with his brief, influential life and work.
 E128329 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: Leah Lee | Statement: [Jules Laforgue, spouse, Leah Lee]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Leah Lee
Context triple: [Jules Laforgue, spouse, Leah Lee]
  • A. Erica Lee
    Erica Lee is a film producer best known for her work on the John Wick action franchise, including John Wick: Chapter 2.
  • B. Gwen May-Wan Kao
    Gwen May-Wan Kao is best known as the wife and long-time partner of Nobel Prize–winning physicist Charles K. Kao, often recognized for supporting his pioneering work in fiber-optic communications.
  • C. Lila Lee
    Lila Lee was a popular American silent film actress of the 1910s and 1920s, known for her girl-next-door charm and roles in major productions of the era.
  • D. Eileen Loo
    Eileen Loo was the wife of renowned Chinese-American architect I. M. Pei and a supportive partner throughout his celebrated career.
  • E. Vivian Chan
    Vivian Chan is a personal name shared by multiple individuals, including professionals in fields such as science, media, and business.
  • 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: Leah Lee
Triple: [Jules Laforgue, spouse, Leah Lee]
Generated description
Leah Lee was the wife of French Symbolist poet Jules Laforgue, known primarily through her association with his brief, influential life and work.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Leah Lee
Target entity description: Leah Lee was the wife of French Symbolist poet Jules Laforgue, known primarily through her association with his brief, influential life and work.
  • A. Erica Lee
    Erica Lee is a film producer best known for her work on the John Wick action franchise, including John Wick: Chapter 2.
  • B. Gwen May-Wan Kao
    Gwen May-Wan Kao is best known as the wife and long-time partner of Nobel Prize–winning physicist Charles K. Kao, often recognized for supporting his pioneering work in fiber-optic communications.
  • C. Lila Lee
    Lila Lee was a popular American silent film actress of the 1910s and 1920s, known for her girl-next-door charm and roles in major productions of the era.
  • D. Eileen Loo
    Eileen Loo was the wife of renowned Chinese-American architect I. M. Pei and a supportive partner throughout his celebrated career.
  • E. Vivian Chan
    Vivian Chan is a personal name shared by multiple individuals, including professionals in fields such as science, media, and business.
  • 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_69a493c476b48190b41fc5e793171cc6 completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4b4c75de88190bf7fec7a053f7a90 completed March 1, 2026, 9:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac537d788c81908d239f102626bdd6 completed March 7, 2026, 4:34 p.m.
NEDg Description generation batch_69ac544fc41881908daff6b313622619 completed March 7, 2026, 4:37 p.m.
NED2 Entity disambiguation (via description) batch_69ac5526679081909c9f7458bd316ff6 completed March 7, 2026, 4:41 p.m.
Created at: March 1, 2026, 7:41 p.m.