Triple

T23357076
Position Surface form Disambiguated ID Type / Status
Subject مدينة أريحا E593077 entity
Predicate nearbyCity P350 FINISHED
Object القدس 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: القدس | Statement: [مدينة أريحا, nearbyCity, القدس]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: القدس
Context triple: [مدينة أريحا, nearbyCity, القدس]
  • 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. 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.
  • E. Jerusalén
    Jerusalén is a small Bolivian municipality located within the La Paz Department in the Andean region of western Bolivia.
  • 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_69e25d24d2a4819092e6ede74c2a918d completed April 17, 2026, 4:17 p.m.
NER Named-entity recognition batch_69f19a18996c81909c7ad15cde616553 completed April 29, 2026, 5:41 a.m.
Created at: April 17, 2026, 5:28 p.m.