Triple

T8525478
Position Surface form Disambiguated ID Type / Status
Subject Nam-gu E201803 entity
Predicate borders P224 FINISHED
Object Ulju-gun E153850 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: Ulju-gun | Statement: [Nam-gu, borders, Ulju-gun]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ulju-gun
Context triple: [Nam-gu, borders, Ulju-gun]
  • A. Ulju-gun chosen
    Ulju-gun is a county-level administrative district located within the metropolitan city of Ulsan in South Korea, known for its mix of industrial facilities and natural landscapes.
  • B. Kakogawa
    Kakogawa is an industrial and residential city in central Hyōgo Prefecture, Japan, known for its steel manufacturing and role as a regional transportation hub.
  • C. Kohlu District
    Kohlu District is an administrative district in the Balochistan province of Pakistan, known for its rugged terrain and predominantly Baloch population.
  • D. Sunpu
    Sunpu is the former name of the Japanese castle town that developed into modern Shizuoka City, historically known as a key stronghold of the Tokugawa shogunate.
  • E. Miura District
    Miura District is a rural administrative district in Kanagawa Prefecture, Japan, known for its coastal towns and scenic Miura Peninsula landscapes.
  • 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_69ca83228b24819085d22e7dc99f5d94 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe644c4648190a14dcaeaa90d72c7 completed March 31, 2026, 3:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69ce4e975d7c8190a7a1fc25c1d67a6f completed April 2, 2026, 11:10 a.m.
Created at: March 30, 2026, 6:16 p.m.