Triple

T16323021
Position Surface form Disambiguated ID Type / Status
Subject Walled Off Hotel E396344 entity
Predicate location P40 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: [Walled Off Hotel, location, Bethlehem]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bethlehem
Context triple: [Walled Off Hotel, location, 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_69d87f255b788190a400eba031dd85d8 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e296b82fe88190a448597b7827f859 completed April 17, 2026, 8:23 p.m.
NED1 Entity disambiguation (via context triple) batch_6a002da0a2908190923e61bdeb92567d completed May 10, 2026, 7:02 a.m.
Created at: April 10, 2026, 5:06 a.m.