Triple

T33582167
Position Surface form Disambiguated ID Type / Status
Subject Night Club E860176 entity
Predicate mainCharacter P1183 FINISHED
Object Amy Chen
Amy Chen is a fictional protagonist known for her central role in the story set around the nightlife world of the work "Night Club."
E2059022 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: Amy Chen | Statement: [Night Club, mainCharacter, Amy Chen]
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: Amy Chen
Triple: [Night Club, mainCharacter, Amy Chen]
Generated description
Amy Chen is a fictional protagonist known for her central role in the story set around the nightlife world of the work "Night Club."

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_69f3497d37848190afcbb5ef3f5c7376 completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f6f77130b0819081ce1fde64afeda2 completed May 3, 2026, 7:21 a.m.
NED1 Entity disambiguation (via context triple) batch_6a361190203c81909a9da6a1e11a62b9 completed June 20, 2026, 4:05 a.m.
NEDg Description generation batch_6a3612901530819082e6fc2d17c1df35 completed June 20, 2026, 4:09 a.m.
NED2 Entity disambiguation (via description) batch_6a361320704c8190a63a2aa5e1f11093 completed June 20, 2026, 4:12 a.m.
Created at: May 1, 2026, 1:40 a.m.