Triple

T12391585
Position Surface form Disambiguated ID Type / Status
Subject Californication E296006 entity
Predicate starring P1507 FINISHED
Object Ellen Woo
Ellen Woo is an actress known for her role in the television series "Californication."
 E982759 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: Ellen Woo | Statement: [Californication, starring, Ellen Woo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Ellen Woo
Context triple: [Californication, starring, Ellen Woo]
  • A. Linda Park
    Linda Park is a Korean-American actress best known for playing communications officer Hoshi Sato on the television series Star Trek: Enterprise.
  • B. Linda Cho
    Linda Cho is a Tony Award–winning costume designer known for her work on major Broadway productions and other theatrical performances.
  • C. Eileen Loo
    Eileen Loo was the wife of renowned Chinese-American architect I. M. Pei and a supportive partner throughout his celebrated career.
  • D. Margaret Chung
    Margaret Chung was a pioneering Chinese American physician and surgeon, widely regarded as the first Chinese American woman doctor in the United States and known for her influential role in supporting U.S. military personnel during World War II.
  • E. Karen Kwan
    Karen Kwan is an American figure skater and the older sister of Olympic medalist Michelle Kwan.
  • 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: Ellen Woo
Triple: [Californication, starring, Ellen Woo]
Generated description
Ellen Woo is an actress known for her role in the television series "Californication."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Ellen Woo
Target entity description: Ellen Woo is an actress known for her role in the television series "Californication."
  • A. Linda Park
    Linda Park is a Korean-American actress best known for playing communications officer Hoshi Sato on the television series Star Trek: Enterprise.
  • B. Linda Cho
    Linda Cho is a Tony Award–winning costume designer known for her work on major Broadway productions and other theatrical performances.
  • C. Eileen Loo
    Eileen Loo was the wife of renowned Chinese-American architect I. M. Pei and a supportive partner throughout his celebrated career.
  • D. Margaret Chung
    Margaret Chung was a pioneering Chinese American physician and surgeon, widely regarded as the first Chinese American woman doctor in the United States and known for her influential role in supporting U.S. military personnel during World War II.
  • E. Karen Kwan
    Karen Kwan is an American figure skater and the older sister of Olympic medalist Michelle Kwan.
  • 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_69d6ad9e653c8190b1473c860ee53dae completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d93fd0bcc48190bb1a59a3aaa6bfdf completed April 10, 2026, 6:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6347c239881909a031e9e195080c9 completed May 2, 2026, 5:29 p.m.
NEDg Description generation batch_69f63674aa3c81908ba82a9d246b3b3a completed May 2, 2026, 5:37 p.m.
NED2 Entity disambiguation (via description) batch_69f63a9b32fc8190ab98492ff91d2a66 completed May 2, 2026, 5:55 p.m.
Created at: April 8, 2026, 9:54 p.m.