Triple

T6144783
Position Surface form Disambiguated ID Type / Status
Subject Henry Barakat E137048 entity
Predicate nativeName P15 FINISHED
Object هنري بركات E556937 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: هنري بركات | Statement: [Henry Barakat, nativeName, هنري بركات]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: هنري بركات
Context triple: [Henry Barakat, nativeName, هنري بركات]
  • A. هنري بركات chosen
    هنري بركات هو مخرج سينمائي مصري بارز يُعد من رواد صناعة الفيلم العربي وقدم العديد من الأعمال الكلاسيكية في تاريخ السينما المصرية.
  • B. Harold Briggs
    Harold Briggs was a British Army officer best known for devising and implementing the Briggs Plan to combat communist insurgency during the Malayan Emergency.
  • C. Walter Hendricks
    Walter Hendricks was an American educator best known as the founder and first president of Marlboro College in Vermont.
  • D. William Heise
    William Heise was an early American cinematographer and camera operator who worked on some of the first motion pictures produced in the late 19th century.
  • E. George Bruns
    George Bruns was an American composer and arranger best known for his work on numerous Disney films and theme park attractions, including iconic scores for animated classics and rides.
  • 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_69c008a2c6308190a56519b22d55d083 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c05cb645508190aea2d77c9de174ba completed March 22, 2026, 9:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69c135fe8ae48190bfb20c335c7d32be completed March 23, 2026, 12:45 p.m.
Created at: March 22, 2026, 4:16 p.m.