Triple

T8335381
Position Surface form Disambiguated ID Type / Status
Subject Annabelle E195774 entity
Predicate musicBy P1952 FINISHED
Object Joseph Bishara E201566 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: Joseph Bishara | Statement: [Annabelle, musicBy, Joseph Bishara]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Joseph Bishara
Context triple: [Annabelle, musicBy, Joseph Bishara]
  • A. Joseph Bishara chosen
    Joseph Bishara is an American composer and actor best known for creating the unsettling musical scores and portraying demonic entities in modern horror films such as those in The Conjuring and Insidious franchises.
  • B. Michel E. Mawad
    Michel E. Mawad is a Lebanese-American physician and academic leader who serves as president of the Lebanese American University.
  • C. Henry Barakat
    Henry Barakat was a prominent Egyptian film director and one of the leading figures of classical Egyptian cinema.
  • D. Eli Samaha
    Eli Samaha is an American film producer known for financing and producing a range of Hollywood genre films, often through independent and mid-budget studio projects.
  • E. Arthur Sadoun
    Arthur Sadoun is a French advertising executive and the chief executive of Publicis Groupe, one of the world’s largest communications and marketing services companies.
  • 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_69ca82ecbdc481908a55cad8ca062d88 completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb7fd2ca648190991e398ba70caf8d completed March 31, 2026, 8:03 a.m.
NED1 Entity disambiguation (via context triple) batch_69cd95d9b92c8190b1eb0e64aa7ea59e completed April 1, 2026, 10:02 p.m.
Created at: March 30, 2026, 5:57 p.m.