Triple

T6486303
Position Surface form Disambiguated ID Type / Status
Subject Princess Sara bint Faisal E146519 entity
Predicate countryOfCitizenship P2 FINISHED
Object Jordan E11658 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: Jordan | Statement: [Princess Sara bint Faisal, countryOfCitizenship, Jordan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jordan
Context triple: [Princess Sara bint Faisal, countryOfCitizenship, Jordan]
  • A. Jordan chosen
    Jordan is a Middle Eastern country located at the crossroads of Asia, Africa, and Europe, known for its ancient archaeological sites like Petra and its strategic political role in the region.
  • B. Jordan
    Jordan is a municipality in the Philippines that serves as the capital of the island province of Guimaras in the Western Visayas region.
  • C. Jordan
    Jordan is a common given name used by people of all genders in many English-speaking and other countries.
  • D. Jordan
    Jordan is a popular Nike-owned athletic footwear and apparel brand originally inspired by basketball legend Michael Jordan and known for its iconic Air Jordan sneakers.
  • E. ערבה
    ערבה היא בקעה מדברית רחבת ידיים בדרום ארץ ישראל וירדן, המשתרעת בין ים המלח למפרץ אילת.
  • 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.