Triple

T7809196
Position Surface form Disambiguated ID Type / Status
Subject The Freshman E180634 entity
Predicate mainCharacter P1183 FINISHED
Object Harold Lamb E679386 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: Harold Lamb | Statement: [The Freshman, mainCharacter, Harold Lamb]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Harold Lamb
Context triple: [The Freshman, mainCharacter, Harold Lamb]
  • A. Harold Lamb chosen
    Harold Lamb was an American historian, novelist, and screenwriter best known for his popular biographies and adventure stories set in Asian and Middle Eastern historical contexts.
  • B. H. M. Harwood
    H. M. Harwood was a British playwright and screenwriter active in the early 20th century, known for his work on stage adaptations and films.
  • C. Walter Connolly
    Walter Connolly was an American character actor of the 1930s known for his comic and often blustery supporting roles in Hollywood films.
  • D. James Norman Hall
    James Norman Hall was an American author and World War I veteran best known for co-writing the classic historical novel "Mutiny on the Bounty" and its sequels.
  • E. Ernest Haycox
    Ernest Haycox was an American author renowned for his prolific and influential Western fiction, several of whose stories were adapted into classic Hollywood films.
  • 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_69ca827f6f148190beca4e245b993506 completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69caf78a6d88819093f83528fe88b182 completed March 30, 2026, 10:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69cb145b93788190a89f26dacbd0b437 completed March 31, 2026, 12:24 a.m.
Created at: March 30, 2026, 4:36 p.m.