Triple

T17405029
Position Surface form Disambiguated ID Type / Status
Subject Sahrij Madrasa (Fes) E423190 entity
Predicate locatedIn P40 FINISHED
Object Fes NE NERFINISHED

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: Fes | Statement: [Sahrij Madrasa (Fes), locatedIn, Fes]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Fes
Context triple: [Sahrij Madrasa (Fes), locatedIn, Fes]
  • A. Fez chosen
    Fez is a historic imperial city in northern Morocco renowned for its well-preserved medieval medina, traditional craftsmanship, and status as a major cultural and religious center.
  • B. Fez
    Fez is the quirky, foreign-exchange student character known for his awkward charm and comedic misunderstandings on the sitcom "That '70s Show."
  • C. Fasa
    Fasa is a city in Iran’s Fars Province known as a regional agricultural and commercial center with historical significance.
  • D. Fira
    Fira is a picturesque town on the Greek island of Santorini, known for its whitewashed buildings, cliffside views over the caldera, and vibrant tourism scene.
  • E. La Febró
    La Febró is a small rural municipality in the Baix Camp comarca of Catalonia, Spain, known for its mountainous landscape and natural surroundings.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d889d7d27c819088486ce3f0627fa1 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e43b068248819088871d79f8a38f30 completed April 19, 2026, 2:16 a.m.
Created at: April 10, 2026, 5:45 a.m.