Triple

T3898693
Position Surface form Disambiguated ID Type / Status
Subject Come and Get It E90433 entity
Predicate starring P1507 FINISHED
Object Edward Arnold E247884 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: Edward Arnold | Statement: [Come and Get It, starring, Edward Arnold]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Edward Arnold
Context triple: [Come and Get It, starring, Edward Arnold]
  • A. Edward Arnold chosen
    Edward Arnold was a prominent American character actor of the early to mid-20th century, known for his powerful screen presence and frequent portrayals of authoritative or villainous figures in Hollywood films.
  • B. Wilfred Lucas
    Wilfred Lucas was a Canadian-born actor and director of the silent film era, known for his work with D. W. Griffith at Biograph Studios.
  • C. Edgar Lansbury
    Edgar Lansbury is a British-born American theatre, film, and television producer known for his work on acclaimed stage productions and as the son of actress Angela Lansbury.
  • D. Godfrey Tearle
    Godfrey Tearle was a distinguished British stage and film actor of the early 20th century, known for his classical Shakespearean roles and appearances in notable films.
  • E. Rupert Baxter
    Rupert Baxter is a recurring character in P. G. Wodehouse’s Blandings Castle stories, known as the hyper-efficient, suspicious former secretary whose attempts to impose order often lead to comic chaos.
  • 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_69aed95d315881908cbf1bf4a7215fbf completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aeecefa3608190a7a20ed6df6a64b2 completed March 9, 2026, 3:53 p.m.
NED1 Entity disambiguation (via context triple) batch_69b53fe99ccc8190849ffe819a4bfd8f completed March 14, 2026, 11 a.m.
Created at: March 9, 2026, 3:21 p.m.