Triple

T13973548
Position Surface form Disambiguated ID Type / Status
Subject Baegu people E336123 entity
Predicate ethnonym P4709 FINISHED
Object Baegu E146329 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: Baegu | Statement: [Baegu people, ethnonym, Baegu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Baegu
Context triple: [Baegu people, ethnonym, Baegu]
  • A. Baeggu chosen
    Baeggu is an Oceanic language of the Meso-Melanesian group spoken by a small community in the Solomon Islands.
  • B. Gojong
    Gojong was the 26th king of the Joseon dynasty and the first emperor of the Korean Empire, ruling during a period of intense foreign intervention and modernization in Korea in the late 19th and early 20th centuries.
  • C. Seochon
    Seochon is a historic neighborhood in central Seoul known for its traditional hanok houses, narrow alleyways, and vibrant mix of old Korean culture and modern cafes and galleries.
  • D. Cheongsapo
    Cheongsapo is a small coastal village in Busan, South Korea, known for its scenic lighthouses, seaside cafes, and ocean views.
  • E. Gukje Sijang
    Gukje Sijang is one of South Korea’s largest and most famous traditional markets, located in Busan and known for its wide variety of goods and bustling atmosphere.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69d81c61f3508190aaf2ca0dc0002c59 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de2e8fd6d48190a157eae8df3a2f3a completed April 14, 2026, 12:09 p.m.
NED1 Entity disambiguation (via context triple) batch_69fba1df334c8190a3d65198cc3d11f6 completed May 6, 2026, 8:17 p.m.
Created at: April 9, 2026, 10:18 p.m.