Triple

T6486326
Position Surface form Disambiguated ID Type / Status
Subject Princess Sara bint Faisal E146519 entity
Predicate residence P75 FINISHED
Object Amman 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 | Statement: [Princess Sara bint Faisal, residence, Amman]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Amman
Context triple: [Princess Sara bint Faisal, residence, Amman]
  • 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. Irbid
    Irbid is a large city in northern Jordan known as an important economic, educational, and cultural center.
  • C. 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.
  • D. 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.
  • E. Aqaba
    Aqaba is Jordan’s only coastal city, a key Red Sea port and popular resort destination known for its beaches, coral reefs, and strategic location near the borders with Israel, Egypt, and Saudi Arabia.
  • 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_69c0090158c08190af0df9a2348d2d52 completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c06a706d4c8190b7a3cc8855abcecb completed March 22, 2026, 10:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6539fe1e08190ae0004ed2113e319 completed March 27, 2026, 9:53 a.m.
Created at: March 22, 2026, 4:52 p.m.