Triple

T13486588
Position Surface form Disambiguated ID Type / Status
Subject A Lot Like Love E318518 entity
Predicate productionCompany P490 FINISHED
Object Beacon Pictures E508528 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: Beacon Pictures | Statement: [A Lot Like Love, productionCompany, Beacon Pictures]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Beacon Pictures
Context triple: [A Lot Like Love, productionCompany, Beacon Pictures]
  • A. Beacon Pictures chosen
    Beacon Pictures is an American film and television production company known for producing a range of high-profile action, thriller, and drama projects in Hollywood.
  • B. Gramercy Pictures
    Gramercy Pictures was an American film production and distribution company known for releasing acclaimed independent and specialty films in the 1990s.
  • C. Embassy Pictures
    Embassy Pictures was an American independent film production and distribution company known for releasing influential and offbeat films from the 1950s through the 1970s.
  • D. Tri-Star Pictures
    Tri-Star Pictures is an American film production and distribution company known for releasing a wide range of Hollywood movies since the 1980s.
  • E. Palace Pictures
    Palace Pictures was a British independent film production and distribution company known for backing influential and unconventional films in the 1980s and early 1990s.
  • 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_69d806b6bfec819089222715b2e86c8e completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69dbaf3a15b48190b63fb59e926a97ae completed April 12, 2026, 2:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69f74638e2088190a126791f60b541c7 completed May 3, 2026, 12:57 p.m.
Created at: April 9, 2026, 9:42 p.m.