Triple

T15680826
Position Surface form Disambiguated ID Type / Status
Subject Helena Augusta E377570 entity
Predicate associatedWith P37 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: [Helena Augusta, associatedWith, Bethlehem]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bethlehem
Context triple: [Helena Augusta, associatedWith, 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 small rural town in western Connecticut known for its historic charm and traditional New England character.
  • 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 suburban town in Albany County, New York, known for its residential communities, schools, and proximity to the city of Albany.
  • 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_69d85cd2e28481909d4e975bee20872f completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04f306a1c8190a819541a3cc51f5a completed April 16, 2026, 2:53 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff6ee2a33c81908fcd120ca670b309 completed May 9, 2026, 5:29 p.m.
Created at: April 10, 2026, 4:16 a.m.