Triple

T31648516
Position Surface form Disambiguated ID Type / Status
Subject Surfside 6 E807652 entity
Predicate hasCharacter P2308 FINISHED
Object Cha Cha O'Brien
Cha Cha O'Brien is a recurring character on the early 1960s detective television series "Surfside 6," known for her involvement with the show's Miami Beach houseboat-based private investigators.
E1971591 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: Cha Cha O'Brien | Statement: [Surfside 6, hasCharacter, Cha Cha O'Brien]
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: Cha Cha O'Brien
Triple: [Surfside 6, hasCharacter, Cha Cha O'Brien]
Generated description
Cha Cha O'Brien is a recurring character on the early 1960s detective television series "Surfside 6," known for her involvement with the show's Miami Beach houseboat-based private investigators.

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_69f348d9ce58819093ea2da83cbeeec1 completed April 30, 2026, 12:19 p.m.
NER Named-entity recognition batch_69f6a957a8cc81909460785e56292bc6 completed May 3, 2026, 1:48 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2b79e1347081908a7a51b49ab23fbd completed June 12, 2026, 3:15 a.m.
NEDg Description generation batch_6a2b7a6983e481908c22bc6844ca0bd2 completed June 12, 2026, 3:18 a.m.
NED2 Entity disambiguation (via description) batch_6a2b7b71012c81909354fe000b507fc9 completed June 12, 2026, 3:22 a.m.
Created at: April 30, 2026, 10:52 p.m.