Triple

T3653539
Position Surface form Disambiguated ID Type / Status
Subject Alex Garland E77475 entity
Predicate wrote P2831 FINISHED
Object The Beach E54669 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: The Beach | Statement: [Alex Garland, wrote, The Beach]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: The Beach
Context triple: [Alex Garland, wrote, The Beach]
  • A. The Beach chosen
    The Beach is a 2000 adventure drama film directed by Danny Boyle, starring Leonardo DiCaprio as a young traveler drawn into a secret island community in Thailand.
  • B. The Beach
    The Beach is the nickname for California State University, Long Beach, a large public university in Southern California known for its diverse student body and coastal campus.
  • C. Beaches (novel)
    Beaches (novel) is a 1985 work of fiction by Iris Rainer Dart that follows the lifelong, emotionally complex friendship between two very different women, later adapted into the popular 1988 film of the same name.
  • D. Silver Beach
    Silver Beach is a famous scenic seaside resort area in Beihai, China, renowned for its fine white sand and gentle coastal waters.
  • E. Twilight Beach
    Twilight Beach is a renowned white-sand beach near Esperance in Western Australia, famous for its turquoise waters, granite rock formations, and excellent swimming conditions.
  • 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_69ad85def5cc8190863dccf55a18bebb completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc3b805a48190a7bc230a382365d6 completed March 8, 2026, 6:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4883bb50c8190bd383b21ac748a2e completed March 13, 2026, 9:57 p.m.
Created at: March 8, 2026, 3:24 p.m.