Triple

T8512732
Position Surface form Disambiguated ID Type / Status
Subject Perelman Theater E201496 entity
Predicate namedAfter P63 FINISHED
Object Raymond G. Perelman E69157 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: Raymond G. Perelman | Statement: [Perelman Theater, namedAfter, Raymond G. Perelman]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Raymond G. Perelman
Context triple: [Perelman Theater, namedAfter, Raymond G. Perelman]
  • A. Raymond G. Perelman chosen
    Raymond G. Perelman was an American businessman and philanthropist known for his major charitable contributions to education, medicine, and the arts, particularly at the University of Pennsylvania.
  • B. Kenneth Posner
    Kenneth Posner is a prominent American theatrical lighting designer known for his work on numerous Broadway productions.
  • C. Roy R. Neuberger
    Roy R. Neuberger was an American financier, philanthropist, and prominent modern art collector who played a key role in supporting and promoting 20th-century artists.
  • D. Daniel H. Lowenstein
    Daniel H. Lowenstein is a prominent American legal scholar known for his pioneering work in election law and political reform.
  • E. Milton J. Rubenstein
    Milton J. Rubenstein was a philanthropist and prominent supporter of science and technology education, for whom the Museum of Science and Technology in Syracuse, New York is named.
  • 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_69ca8320e5748190ac2c585a0bba8193 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe60b0d4c8190812ddbc1c17389c8 completed March 31, 2026, 3:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69ce4e4e64f481908ddf99570fe59332 completed April 2, 2026, 11:09 a.m.
Created at: March 30, 2026, 6:15 p.m.