Triple

T1079489
Position Surface form Disambiguated ID Type / Status
Subject President of Singapore E23914 entity
Predicate seat P75 FINISHED
Object The Istana E123103 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: The Istana | Statement: [President of Singapore, seat, The Istana]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: The Istana
Context triple: [President of Singapore, seat, The Istana]
  • A. The Istana chosen
    The Istana is the official presidential palace and primary ceremonial venue of Singapore, serving as the office and residence of the President.
  • B. Haga Palace
    Haga Palace is a historic royal residence in Sweden, located within Haga Park just north of central Stockholm.
  • C. Anif Palace
    Anif Palace is a historic 19th-century neo-Gothic castle near Salzburg, Austria, known for its picturesque lakeside setting and use as a filming location.
  • D. Sheen Palace
    Sheen Palace was a medieval royal residence on the River Thames in Surrey that served as a favored home of English monarchs, including Edward III, before later being rebuilt as Richmond Palace.
  • E. Gedung Sate
    Gedung Sate is a historic government building in Bandung, Indonesia, renowned for its unique Indo-European architectural style and iconic central "satay skewer" tower.
  • 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_69a493f1ddf48190a99d54b00e99f8ce completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4b94509d08190964509ea4a2d7912 completed March 1, 2026, 10:10 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac4c2247888190a7ab75b447b4773f completed March 7, 2026, 4:02 p.m.
Created at: March 1, 2026, 7:42 p.m.