Triple

T18525612
Position Surface form Disambiguated ID Type / Status
Subject Gedong Sate E452709 entity
Predicate nickname P55 FINISHED
Object Satay Building 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: Satay Building | Statement: [Gedong Sate, nickname, Satay Building]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Satay Building
Context triple: [Gedong Sate, nickname, Satay Building]
  • A. Satay Building chosen
    Satay Building is a landmark government building in Bandung, Indonesia, famed for its distinctive central pinnacle that resembles skewered satay.
  • B. Perelman Building
    The Perelman Building is an annex of the Philadelphia Museum of Art known for its Art Deco architecture and galleries dedicated to modern and contemporary design, prints, drawings, and photography.
  • C. Nassif Building
    The Nassif Building is a prominent federal office building in Washington, D.C., best known for long serving as the main headquarters of the U.S. Department of Transportation.
  • D. Salamon Tower
    Salamon Tower is a medieval defensive tower and prominent historical monument in the town of Visegrád, Hungary.
  • E. Manasseh Meyer Building
    The Manasseh Meyer Building is a key academic facility of the Lee Kuan Yew School of Public Policy at the National University of Singapore, housing classrooms, offices, and spaces for policy research and education.
  • 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_69d8d387b5548190aa030dad2cb4947e completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e533914e808190a46638de1ce2d57b completed April 19, 2026, 7:57 p.m.
Created at: April 10, 2026, 11:37 a.m.