Triple

T22003912
Position Surface form Disambiguated ID Type / Status
Subject Along with the Gods: The Two Worlds E543401 entity
Predicate director P255 FINISHED
Object Kim Yong-hwa
Kim Yong-hwa is a South Korean film director and screenwriter known for commercially successful and effects-heavy hits such as the Along with the Gods series and 200 Pounds Beauty.
E1868592 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: Kim Yong-hwa | Statement: [Along with the Gods: The Two Worlds, director, Kim Yong-hwa]
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: Kim Yong-hwa
Triple: [Along with the Gods: The Two Worlds, director, Kim Yong-hwa]
Generated description
Kim Yong-hwa is a South Korean film director and screenwriter known for commercially successful and effects-heavy hits such as the Along with the Gods series and 200 Pounds Beauty.

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_69e11e2c814c8190837d072789000486 completed April 16, 2026, 5:36 p.m.
NER Named-entity recognition batch_69f1276cab5c8190ac1236fde7e0394a completed April 28, 2026, 9:32 p.m.
NED1 Entity disambiguation (via context triple) batch_6a25f0e0f5808190bd6d7722f1e98c40 completed June 7, 2026, 10:29 p.m.
NEDg Description generation batch_6a25f597671881908e6321f3a9d8be7c completed June 7, 2026, 10:49 p.m.
NED2 Entity disambiguation (via description) batch_6a25f9567c1081908688ac7813b817f4 completed June 7, 2026, 11:05 p.m.
Created at: April 16, 2026, 8:20 p.m.