Triple

T16558155
Position Surface form Disambiguated ID Type / Status
Subject Biblical places E402262 entity
Predicate hasExample P1259 FINISHED
Object Bethlehem E8382 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: Bethlehem | Statement: [Biblical places, hasExample, Bethlehem]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bethlehem
Context triple: [Biblical places, hasExample, Bethlehem]
  • A. Bethlehem chosen
    Bethlehem is an ancient town in the West Bank historically revered as the birthplace of Jesus and a major center of Christian pilgrimage.
  • B. Bethlehem
    Bethlehem is a suburban town in Albany County, New York, known for its residential communities, schools, and proximity to the city of Albany.
  • C. Bethlehem
    Bethlehem is a historic city in eastern Pennsylvania known for its former steel industry, vibrant arts scene, and role as home to Lehigh University.
  • D. Bethlehem
    Bethlehem is a small rural town in western Connecticut known for its historic charm and traditional New England character.
  • E. Bethlehem of Galilee
    Bethlehem of Galilee is a village in northern Israel originally established as a German Templer agricultural colony in the late 19th century.
  • 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_69d8838648088190acf97ef11fc3f61b completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e3576bce0c819087ab36f7dec5c394 completed April 18, 2026, 10:05 a.m.
NED1 Entity disambiguation (via context triple) batch_6a006eddb01081908e7ab59264199e15 completed May 10, 2026, 11:41 a.m.
Created at: April 10, 2026, 5:15 a.m.