Triple

T6328214
Position Surface form Disambiguated ID Type / Status
Subject Green–Schwarz mechanism E141910 entity
Predicate namedAfter P63 FINISHED
Object Michael Green E26834 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: Michael Green | Statement: [Green–Schwarz mechanism, namedAfter, Michael Green]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Michael Green
Context triple: [Green–Schwarz mechanism, namedAfter, Michael Green]
  • A. Michael Green
    Michael Green is an American screenwriter and producer known for his work on major films and television series, including projects like "Logan," "Blade Runner 2049," and "American Gods."
  • B. Michael Green chosen
    Michael Green is a prominent British theoretical physicist known for his pioneering work in string theory and quantum gravity.
  • C. David M. Green
    David M. Green is a distinguished figure in the field of acoustics recognized for his significant contributions with the prestigious ASA Gold Medal.
  • D. Michael V. Drake
    Michael V. Drake is an American academic leader and physician who has served as president of both The Ohio State University and the University of California system.
  • E. Michael Filerman
    Michael Filerman was an American television producer best known for developing and producing popular prime-time soap operas during the 1970s and 1980s.
  • 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_69c008d201748190917e69c41ba3f978 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c0651197908190a30e504e2442d40f completed March 22, 2026, 9:54 p.m.
NED1 Entity disambiguation (via context triple) batch_69c60410223081908c1cf3663d4b14c0 completed March 27, 2026, 4:14 a.m.
Created at: March 22, 2026, 4:29 p.m.