Triple

T3136630
Position Surface form Disambiguated ID Type / Status
Subject Eileen Loo E65546 entity
Predicate name P16 FINISHED
Object Eileen Loo
Eileen Loo is an individual whose specific public background or notable achievements are not clearly established from the available information.
 E65546 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: Eileen Loo | Statement: [Eileen Loo, name, Eileen Loo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Eileen Loo
Context triple: [Eileen Loo, name, Eileen Loo]
  • A. Eileen Loo
    Eileen Loo was the wife of renowned Chinese-American architect I. M. Pei and a supportive partner throughout his celebrated career.
  • B. Janet Lam
    Janet Lam is known as the wife of John Lee Ka-chiu, the Chief Executive of Hong Kong.
  • C. Karen Kwan
    Karen Kwan is an American figure skater and the older sister of Olympic medalist Michelle Kwan.
  • D. Rosalie Chiang
    Rosalie Chiang is an American actress best known for voicing the main character, Meilin "Mei" Lee, in Pixar's animated film "Turning Red."
  • E. Lori Huang
    Lori Huang is the wife of NVIDIA co-founder and CEO Jensen Huang and is known for her low public profile despite her connection to the prominent tech executive.
  • 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: Eileen Loo
Triple: [Eileen Loo, name, Eileen Loo]
Generated description
Eileen Loo is an individual whose specific public background or notable achievements are not clearly established from the available information.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Eileen Loo
Target entity description: Eileen Loo is an individual whose specific public background or notable achievements are not clearly established from the available information.
  • A. Eileen Loo chosen
    Eileen Loo was the wife of renowned Chinese-American architect I. M. Pei and a supportive partner throughout his celebrated career.
  • B. Janet Lam
    Janet Lam is known as the wife of John Lee Ka-chiu, the Chief Executive of Hong Kong.
  • C. Karen Kwan
    Karen Kwan is an American figure skater and the older sister of Olympic medalist Michelle Kwan.
  • D. Rosalie Chiang
    Rosalie Chiang is an American actress best known for voicing the main character, Meilin "Mei" Lee, in Pixar's animated film "Turning Red."
  • E. Lori Huang
    Lori Huang is the wife of NVIDIA co-founder and CEO Jensen Huang and is known for her low public profile despite her connection to the prominent tech executive.
  • F. None of above.

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_69ad8581c25c8190b0d85ba9b9baa531 completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ada564eacc8190a54d07b4eb31c196 completed March 8, 2026, 4:35 p.m.
NED1 Entity disambiguation (via context triple) batch_69b261f805b0819089bf8a94c331faf1 completed March 12, 2026, 6:49 a.m.
NEDg Description generation batch_69b2669184888190acd08d3286479907 completed March 12, 2026, 7:09 a.m.
NED2 Entity disambiguation (via description) batch_69b266f1bef48190afeca90e35918fe3 completed March 12, 2026, 7:10 a.m.
Created at: March 8, 2026, 3:05 p.m.