Triple

T18731458
Position Surface form Disambiguated ID Type / Status
Subject Pachinko E458043 entity
Predicate character P662 FINISHED
Object Sunja NE NERFINISHED

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: Sunja | Statement: [Pachinko, character, Sunja]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sunja
Context triple: [Pachinko, character, Sunja]
  • A. Sunja chosen
    Sunja is a resilient Korean woman whose life, marked by sacrifice, love, and survival across generations and countries, forms the emotional core of Min Jin Lee’s novel "Pachinko."
  • B. Sojin
    Sojin is a given name, often used in East Asian cultures, that can refer to various individuals in entertainment, arts, and other fields.
  • C. Sijjin
    Sijjin is an Islamic term referring to a record or register in which the deeds of the wicked are inscribed and a place associated with severe punishment in the Hereafter.
  • D. Maeng-hee
    Maeng-hee is a Korean given name, notably borne by individuals such as businessman Lee Maeng-hee.
  • E. Hosuni
    Hosuni is the female tiger mascot character created as the sibling counterpart to Hodori, the official mascot of the 1988 Seoul Olympic Games.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8d393ba9c8190a8b03b04ddbb0a09 completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e56d7854748190b66c4aaadfd67f29 completed April 20, 2026, 12:04 a.m.
Created at: April 10, 2026, 11:51 a.m.