Triple

T16359868
Position Surface form Disambiguated ID Type / Status
Subject Kingdom of Jerusalem coat of arms E397281 entity
Predicate associatedWith P37 FINISHED
Object Jerusalem E6995 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: Jerusalem | Statement: [Kingdom of Jerusalem coat of arms, associatedWith, Jerusalem]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jerusalem
Context triple: [Kingdom of Jerusalem coat of arms, associatedWith, 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 town in Yates County, New York, known for its rural character and location in the Finger Lakes region.
  • C. 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.
  • 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. Jerusalem city center
    Jerusalem city center is the main commercial and cultural hub of Jerusalem, featuring busy shopping streets, historic sites, and key public institutions.
  • 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_69d87f2778dc8190aa95c7572db127e6 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e2fad241848190a9f32c7b050f20a5 completed April 18, 2026, 3:30 a.m.
NED1 Entity disambiguation (via context triple) batch_6a002dbce2508190b655de87f48e841e completed May 10, 2026, 7:03 a.m.
Created at: April 10, 2026, 5:07 a.m.