Triple

T7503107
Position Surface form Disambiguated ID Type / Status
Subject Princess Noor bint Asem E177314 entity
Predicate placeOfBirth P1 FINISHED
Object Amman, Jordan E15311 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: Amman, Jordan | Statement: [Princess Noor bint Asem, placeOfBirth, Amman, Jordan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Amman, Jordan
Context triple: [Princess Noor bint Asem, placeOfBirth, Amman, Jordan]
  • A. Amman chosen
    Amman is the capital and largest city of Jordan, serving as a major political, economic, and cultural center in the Arab world.
  • B. Ma’an
    Ma’an is a major city in southern Jordan that serves as an important regional hub and gateway to nearby desert and archaeological sites.
  • C. Dhiban, Jordan
    Dhiban, Jordan is an archaeological town in central Jordan best known as the ancient Moabite city of Dibon, where the famous Mesha Stele was discovered.
  • D. Irbid
    Irbid is a large city in northern Jordan known as an important economic, educational, and cultural center.
  • E. Mafraq
    Mafraq is a city in northern Jordan that serves as a strategic transport hub and gateway to the Syrian border and surrounding desert regions.
  • 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_69c69f2696688190915a8458f2398211 completed March 27, 2026, 3:15 p.m.
NER Named-entity recognition batch_69c6f5b32c708190bb3a92d0d949304a completed March 27, 2026, 9:25 p.m.
NED1 Entity disambiguation (via context triple) batch_69c83c9953e88190a1e0e899f2ddf822 completed March 28, 2026, 8:39 p.m.
Created at: March 27, 2026, 3:44 p.m.