Triple

T12316547
Position Surface form Disambiguated ID Type / Status
Subject Emir Shakib Arslan E293614 entity
Predicate birthPlace P1 FINISHED
Object Mount Lebanon E59382 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: Mount Lebanon | Statement: [Emir Shakib Arslan, birthPlace, Mount Lebanon]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mount Lebanon
Context triple: [Emir Shakib Arslan, birthPlace, Mount Lebanon]
  • A. Mount Lebanon chosen
    Mount Lebanon is a historic mountainous region in modern-day Lebanon that has long served as a cultural and political heartland for the Druze community.
  • B. North Lebanon
    North Lebanon is a region in northern Lebanon that was a significant theater of conflict and political tension during the Lebanese Civil War.
  • C. Mt. Lebanon
    Mt. Lebanon is a suburban municipality just south of Pittsburgh, Pennsylvania, known for its residential neighborhoods, strong school system, and walkable business districts.
  • D. Mount Carmel
    Mount Carmel is a coastal mountain range in northern Israel known for its religious significance, scenic landscapes, and the city of Haifa built on its slopes.
  • E. Mount Carmel
    Mount Carmel is a residential neighborhood in Hamden, Connecticut, known for its proximity to Sleeping Giant State Park and Quinnipiac University.
  • 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_69d6ab6a2b50819082f6aedd32ed608a completed April 8, 2026, 7:24 p.m.
NER Named-entity recognition batch_69d93f05186481909c024a933b4f6c60 completed April 10, 2026, 6:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6685205608190b504ab6e7c73ee51 completed May 2, 2026, 9:10 p.m.
Created at: April 8, 2026, 9:53 p.m.