Triple

T20010431
Position Surface form Disambiguated ID Type / Status
Subject Beth Zur E494574 entity
Predicate near P350 FINISHED
Object Jerusalem NE NERFINISHED

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: Jerusalem | Statement: [Beth Zur, near, Jerusalem]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jerusalem
Context triple: [Beth Zur, near, Jerusalem]
  • A. Jerusalem chosen
    Jerusalem is an ancient and historically significant city in the Middle East that serves as a major religious and cultural center for Judaism, Christianity, and Islam.
  • B. Jerusalem
    Jerusalem is a novel by Swedish author Selma Lagerlöf that portrays the lives, faith, and emigration of a group of Swedish villagers who journey to the Holy Land.
  • C. Jerusalem
    Jerusalem is a town in Yates County, New York, known for its rural character and location in the Finger Lakes region.
  • D. Jerusalén
    Jerusalén is a small Bolivian municipality located within the La Paz Department in the Andean region of western Bolivia.
  • E. Jesusalém
    Jesusalém is a novel by Mozambican writer Mia Couto that explores memory, war, and identity through a boy’s life in an isolated, post-conflict African landscape.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69da626b2d748190886981ea90c8b2ea completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e662362df48190abf16129eea39985 completed April 20, 2026, 5:28 p.m.
Created at: April 11, 2026, 3:33 p.m.