Triple

T6872253
Position Surface form Disambiguated ID Type / Status
Subject Prince Hassan bin Talal E158577 entity
Predicate country of citizenship 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: [Prince Hassan bin Talal, country of citizenship, Jordan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jordan
Context triple: [Prince Hassan bin Talal, country of citizenship, Jordan]
  • A. Jordan
    Jordan is a municipality in the Philippines that serves as the capital of the island province of Guimaras in the Western Visayas region.
  • B. Jordan
    Jordan was a Formula One racing team and constructor known for launching the careers of several top drivers and competing in the sport during the 1990s and early 2000s.
  • C. 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.
  • 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. Jordan
    Jordan is a common given name used by people of all genders in many English-speaking and other countries.
  • 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_69c68832af1481908ce356e133ebaebe completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d8ac04e08190aa8011c0ade9d509 completed March 27, 2026, 7:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69c742af0df88190bb23b7495c279e08 completed March 28, 2026, 2:53 a.m.
Created at: March 27, 2026, 2:22 p.m.