Triple

T23436241
Position Surface form Disambiguated ID Type / Status
Subject The Worst of Evil E563467 entity
Predicate hasCharacter P2308 FINISHED
Object Yoo Eui-jung
Yoo Eui-jung is a character in the South Korean crime-action drama series "The Worst of Evil," which centers on undercover investigations into a powerful drug cartel.
E1923333 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: Yoo Eui-jung | Statement: [The Worst of Evil, hasCharacter, Yoo Eui-jung]
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: Yoo Eui-jung
Triple: [The Worst of Evil, hasCharacter, Yoo Eui-jung]
Generated description
Yoo Eui-jung is a character in the South Korean crime-action drama series "The Worst of Evil," which centers on undercover investigations into a powerful drug cartel.

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_69e24553980c8190bb66a2ae0bdab125 completed April 17, 2026, 2:36 p.m.
NER Named-entity recognition batch_69f1a5dbdf248190a09e971f2718d01f completed April 29, 2026, 6:31 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2863aaf76881909b9ee85edfa2bdbe completed June 9, 2026, 7:04 p.m.
NEDg Description generation batch_6a2866c192088190a41c695f10cd238d completed June 9, 2026, 7:17 p.m.
NED2 Entity disambiguation (via description) batch_6a286737b96c8190a559e995190ab7cb completed June 9, 2026, 7:19 p.m.
Created at: April 17, 2026, 5:50 p.m.