Triple

T15996461
Position Surface form Disambiguated ID Type / Status
Subject Dr. Mark Greene E387977 entity
Predicate hasRelationshipWith P2830 FINISHED
Object Susan Lewis E517213 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: Susan Lewis | Statement: [Dr. Mark Greene, hasRelationshipWith, Susan Lewis]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Susan Lewis
Context triple: [Dr. Mark Greene, hasRelationshipWith, Susan Lewis]
  • A. Susan Lewis chosen
    Susan Lewis is a fictional emergency physician and central character on the television series "ER," known for her dedication, compassion, and complex personal storylines.
  • B. Susie Lewis
    Susie Lewis is an animator and producer best known for her work on the MTV animated series "Daria."
  • C. Karen Lewis
    Karen Lewis is a film and television producer known for her work on the project "Exile."
  • D. Karen Lewis
    Karen Lewis is a television producer known for her work on the British drama series "Years and Years."
  • E. Karen Lewis
    Karen Lewis is a British television producer best known for her work on acclaimed drama series such as "Last Tango in Halifax."
  • 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_69d86daa562c81908aacc179c0fe8fb5 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e157882ef0819081143e530bd6413c completed April 16, 2026, 9:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69ffcf1edc7c81908fdd0fa00418d7a7 completed May 10, 2026, 12:19 a.m.
Created at: April 10, 2026, 4:55 a.m.