Triple

T33126558
Position Surface form Disambiguated ID Type / Status
Subject South Korea national baseball team E847737 entity
Predicate notablePlayer P304 FINISHED
Object Choo Shin-soo
Choo Shin-soo is a South Korean professional baseball outfielder known for his successful Major League Baseball career and key contributions to international competitions for South Korea.
E2287256 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: Choo Shin-soo | Statement: [South Korea national baseball team, notablePlayer, Choo Shin-soo]
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: Choo Shin-soo
Triple: [South Korea national baseball team, notablePlayer, Choo Shin-soo]
Generated description
Choo Shin-soo is a South Korean professional baseball outfielder known for his successful Major League Baseball career and key contributions to international competitions for South 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_69f349588f088190b7c9588860f72033 completed April 30, 2026, 12:21 p.m.
NER Named-entity recognition batch_69f6d7205a588190af68e11ec875402d completed May 3, 2026, 5:03 a.m.
NED1 Entity disambiguation (via context triple) batch_6a4772cd44e48190852fe80ae95cf978 completed July 3, 2026, 8:29 a.m.
NEDg Description generation batch_6a47745193708190a0eb5004fbfb4f73 completed July 3, 2026, 8:35 a.m.
NED2 Entity disambiguation (via description) batch_6a4776fdfba8819089631b6b366b818e completed July 3, 2026, 8:46 a.m.
Created at: May 1, 2026, 1:27 a.m.