Triple

T21869284
Position Surface form Disambiguated ID Type / Status
Subject Golden Age of Korean cinema E539961 entity
Predicate notableDirector P4744 FINISHED
Object Shin Sang-ok
Shin Sang-ok was a prominent South Korean film director and producer, often called the “Prince of Korean Cinema,” known for his influential work during the mid-20th century and his dramatic abduction to North Korea.
E1730214 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: Shin Sang-ok | Statement: [Golden Age of Korean cinema, notableDirector, Shin Sang-ok]
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: Shin Sang-ok
Triple: [Golden Age of Korean cinema, notableDirector, Shin Sang-ok]
Generated description
Shin Sang-ok was a prominent South Korean film director and producer, often called the “Prince of Korean Cinema,” known for his influential work during the mid-20th century and his dramatic abduction to North Korea.

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_69e0c478f59081909d54302b57fc1ce3 completed April 16, 2026, 11:14 a.m.
NER Named-entity recognition batch_69f0f334362c819094af465ee57b47e6 completed April 28, 2026, 5:49 p.m.
NED1 Entity disambiguation (via context triple) batch_6a11c7d5af2c8190a2850758c33a45d1 completed May 23, 2026, 3:29 p.m.
NEDg Description generation batch_6a11c85c8a208190b4afaaa039b12c6c completed May 23, 2026, 3:31 p.m.
NED2 Entity disambiguation (via description) batch_6a11c9206c588190a43338df1f2e4d88 completed May 23, 2026, 3:34 p.m.
Created at: April 16, 2026, 6:57 p.m.