Triple

T3790776
Position Surface form Disambiguated ID Type / Status
Subject Joachim Murat E89640 entity
Predicate familyName P18 FINISHED
Object Murat E301498 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: Murat | Statement: [Joachim Murat, familyName, Murat]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Murat
Context triple: [Joachim Murat, familyName, Murat]
  • A. Murat chosen
    Murat is a historic small town in south-central France, known for its volcanic landscape setting in the Cantal region and its traditional stone architecture.
  • B. Mehmet
    Mehmet is a common Turkish male given name of Arabic origin, widely used across Turkey and among Turkish communities.
  • C. Murad Bey
    Murad Bey was a prominent Mamluk military leader and ruler in late 18th-century Egypt who fiercely resisted Napoleon’s invasion.
  • D. Ahmet
    Ahmet is a common male given name of Arabic origin, widely used in Turkey and other Muslim-majority countries as a variant of Ahmed.
  • E. Orhan Gazi
    Orhan Gazi was the second ruler of the Ottoman Beylik who significantly expanded its territories in northwestern Anatolia during the 14th century, laying foundations for the future Ottoman Empire.
  • 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_69aed9597d6881909b6ee3b9de859223 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aee7687c4481908d5e6988e2638b68 completed March 9, 2026, 3:29 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4f055e3988190a1b3633e390c0d6f completed March 14, 2026, 5:21 a.m.
Created at: March 9, 2026, 3:15 p.m.