Triple

T3519663
Position Surface form Disambiguated ID Type / Status
Subject Henry Golding E74388 entity
Predicate spouse P13 FINISHED
Object Liv Lo
Liv Lo is a Taiwanese television host, fitness entrepreneur, and yoga instructor known for her work in wellness and as the wife of actor Henry Golding.
 E366066 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: Liv Lo | Statement: [Henry Golding, spouse, Liv Lo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Liv Lo
Context triple: [Henry Golding, spouse, Liv Lo]
  • A. Liv
    Liv is a feminine given name, often used in Scandinavian countries and popularized internationally by actress Liv Tyler.
  • B. Lori
    Lori is a feminine given name commonly used in English-speaking countries, often as a diminutive of Laura or Lorraine.
  • C. Lulu
    Lulu is a common feminine given name or nickname, often used as a diminutive form of names like Louise.
  • D. Lana
    Lana is the seductive call girl who becomes the central love interest and catalyst for chaos in the 1983 film "Risky Business."
  • E. Lola Lane
    Lola Lane was an American film actress best known as one of the Lane Sisters, who appeared in numerous Hollywood productions during the 1930s and 1940s.
  • 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: Liv Lo
Triple: [Henry Golding, spouse, Liv Lo]
Generated description
Liv Lo is a Taiwanese television host, fitness entrepreneur, and yoga instructor known for her work in wellness and as the wife of actor Henry Golding.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Liv Lo
Target entity description: Liv Lo is a Taiwanese television host, fitness entrepreneur, and yoga instructor known for her work in wellness and as the wife of actor Henry Golding.
  • A. Liv
    Liv is a feminine given name, often used in Scandinavian countries and popularized internationally by actress Liv Tyler.
  • B. Lori
    Lori is a feminine given name commonly used in English-speaking countries, often as a diminutive of Laura or Lorraine.
  • C. Lulu
    Lulu is a common feminine given name or nickname, often used as a diminutive form of names like Louise.
  • D. Lana
    Lana is the seductive call girl who becomes the central love interest and catalyst for chaos in the 1983 film "Risky Business."
  • E. Lola Lane
    Lola Lane was an American film actress best known as one of the Lane Sisters, who appeared in numerous Hollywood productions during the 1930s and 1940s.
  • 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_69ad85cfb5c881909c9a2edd9d6043cc completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adbc4af70c8190a7471f28e1efd7fd completed March 8, 2026, 6:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69b37e848d1c8190b100cb2e1218afbb completed March 13, 2026, 3:03 a.m.
NEDg Description generation batch_69b37f07ab70819089fdb7083b81b992 completed March 13, 2026, 3:05 a.m.
NED2 Entity disambiguation (via description) batch_69b38078bc288190b69d73a64acce8ca completed March 13, 2026, 3:11 a.m.
Created at: March 8, 2026, 3:19 p.m.