Triple

T19478621
Position Surface form Disambiguated ID Type / Status
Subject Names of Singapore E487318 entity
Predicate hasHistoricalName P2834 FINISHED
Object Singapura 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: Singapura | Statement: [Names of Singapore, hasHistoricalName, Singapura]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Singapura
Context triple: [Names of Singapore, hasHistoricalName, Singapura]
  • A. Lingapura
    Lingapura is the ancient name for Koh Ker, a 10th-century Khmer temple complex and former capital of the Khmer Empire in northern Cambodia.
  • B. Singapore chosen
    Singapore is a sovereign city-state and island nation in Southeast Asia known for its global financial hub status, multicultural society, and highly developed, efficient infrastructure.
  • C. Singhpur
    Singhpur is a historical town that served as the capital of the Sikh Singhpuria Misl confederacy in Punjab.
  • D. Lion City
    Lion City is a popular nickname for Singapore, reflecting its legendary origins and status as a powerful, modern city-state.
  • E. Singa city
    Singa city is the capital of Sudan’s Sennar State, serving as an important administrative and commercial center along the Blue Nile.
  • 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_69d8e8d924388190b847cb15bb3d0aff completed April 10, 2026, 12:11 p.m.
NER Named-entity recognition batch_69e63437b9748190a8fc6bf6b3d90918 completed April 20, 2026, 2:12 p.m.
Created at: April 10, 2026, 1:39 p.m.