Triple

T26523370
Position Surface form Disambiguated ID Type / Status
Subject Hangin' with Mr. Cooper E670619 entity
Predicate featuresCharacter P626 FINISHED
Object Nicole Lee
Nicole Lee is a young, spirited supporting character on the 1990s American sitcom "Hangin' with Mr. Cooper," known for her close relationship with the show's main characters and her presence in the household's comedic dynamics.
E1831097 NE FINISHED

How this triple was built (2 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: Nicole Lee | Statement: [Hangin' with Mr. Cooper, featuresCharacter, Nicole Lee]
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: Nicole Lee
Triple: [Hangin' with Mr. Cooper, featuresCharacter, Nicole Lee]
Generated description
Nicole Lee is a young, spirited supporting character on the 1990s American sitcom "Hangin' with Mr. Cooper," known for her close relationship with the show's main characters and her presence in the household's comedic dynamics.

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_69eeb31ea1e08190b9ff43cf9bc25bf8 completed April 27, 2026, 12:51 a.m.
NER Named-entity recognition batch_69f613c430148190b0c42d341d5bde09 completed May 2, 2026, 3:09 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1ccf08ca6081909f7294dc073f7136 completed June 1, 2026, 12:15 a.m.
NEDg Description generation batch_6a1ccff86fc88190b1438e77f3a5f101 completed June 1, 2026, 12:19 a.m.
NED2 Entity disambiguation (via description) batch_6a24946ccd908190ae144fbc7010aca9 completed June 6, 2026, 9:43 p.m.
Created at: April 27, 2026, 1:29 a.m.