Triple

T1967233
Position Surface form Disambiguated ID Type / Status
Subject Jordanian dinar E42716 entity
Predicate usedIn P98 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: [Jordanian dinar, usedIn, Jordan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jordan
Context triple: [Jordanian dinar, usedIn, 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 popular Nike-owned athletic footwear and apparel brand originally inspired by basketball legend Michael Jordan and known for its iconic Air Jordan sneakers.
  • C. Jordanes
    Jordanes was a 6th-century Roman bureaucrat and historian best known for his work "Getica," a key source on the history of the Goths and other barbarian peoples.
  • D. Masri
    Masri is a widely spoken modern Arabic dialect used primarily in Egypt, especially in everyday conversation and popular media.
  • E. Suriya
    Suriya is a prominent Indian actor and producer best known for his versatile performances in Tamil cinema across action, drama, and socially themed films.
  • 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_69a88711151c8190940b2572095059d7 completed March 4, 2026, 7:25 p.m.
NER Named-entity recognition batch_69abb3cf15048190a51f73ed85e1b958 completed March 7, 2026, 5:12 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae0acd9c3c8190a6f1140a7fac1627 completed March 8, 2026, 11:48 p.m.
Created at: March 4, 2026, 7:36 p.m.