Triple

T3056777
Position Surface form Disambiguated ID Type / Status
Subject Midrand E60499 entity
Predicate hasSuburb P747 FINISHED
Object President Park E253062 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: President Park | Statement: [Midrand, hasSuburb, President Park]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: President Park
Context triple: [Midrand, hasSuburb, President Park]
  • A. Moon Jae-in
    Moon Jae-in is a South Korean politician and former human rights lawyer who served as the President of South Korea from 2017 to 2022.
  • B. John Kim
    John Kim is an Australian actor best known for his role as Ezekiel Jones in the fantasy-adventure television series "The Librarians."
  • C. John Kim
    John Kim is a prominent mechanical engineer and researcher renowned for his pioneering work in computational fluid dynamics and turbulence modeling.
  • D. Lee Myung-bak
    Lee Myung-bak is a South Korean businessman-turned-politician who served as the President of South Korea from 2008 to 2013.
  • E. Park Geun-hye chosen
    Park Geun-hye is a South Korean politician who served as the country’s first female president from 2013 until her impeachment and removal from office in 2017.
  • 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_69ad8578137c81908259dcb27c7d6d7c completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ad9e13f16c81909e11ed1444c71151 completed March 8, 2026, 4:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69b1ef0671e48190a793f907cc211dd8 completed March 11, 2026, 10:39 p.m.
Created at: March 8, 2026, 3:02 p.m.