Triple

T12115721
Position Surface form Disambiguated ID Type / Status
Subject Amanda Abbington E288554 entity
Predicate notableWork P4 FINISHED
Object Safe E734495 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: Safe | Statement: [Amanda Abbington, notableWork, Safe]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Safe
Context triple: [Amanda Abbington, notableWork, Safe]
  • A. Safe
    Safe is a 1995 psychological drama film directed by Todd Haynes, in which Julianne Moore plays a suburban housewife who develops a mysterious environmental illness, exploring themes of alienation, illness, and societal anxiety.
  • B. Safe chosen
    Safe is a 2012 action thriller film starring Jason Statham as a former elite agent who protects a young girl with a memorized code sought by the Triads, the Russian mob, and corrupt officials.
  • C. SAFE
    SAFE (Saving Animals From Extinction) is a conservation initiative dedicated to protecting and recovering endangered animal species and their habitats.
  • D. SAFE
    SAFE is a World Customs Organization framework that sets global standards to enhance the security and efficiency of international trade and supply chains.
  • E. Safer
    Safer is the surname of Morley Safer, the renowned Canadian-American broadcast journalist best known for his long tenure as a correspondent on CBS's 60 Minutes.
  • 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_69d6ab4a5c448190a110d1273314b21a completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d9156921dc8190aa132b0ab3a7c184 completed April 10, 2026, 3:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69f5f67f9c30819089305d5d42210c34 completed May 2, 2026, 1:05 p.m.
Created at: April 8, 2026, 9:49 p.m.