Triple

T15583723
Position Surface form Disambiguated ID Type / Status
Subject Razihi dialect E374564 entity
Predicate hasAlternativeName P39 FINISHED
Object Razihi E378252 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: Razihi | Statement: [Razihi dialect, hasAlternativeName, Razihi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Razihi
Context triple: [Razihi dialect, hasAlternativeName, Razihi]
  • A. Razihi chosen
    Razihi is a highly divergent Arabic-related language spoken by a small community in the mountainous Jabal Razih region of northwestern Yemen.
  • B. Khudayar
    Khudayar is a male given name most notably associated with Khudayar Khan, a 19th-century ruler of the Khanate of Kokand in Central Asia.
  • C. Makhshirin
    Makhshirin is a tractate of the Mishnah in Seder Tohorot that deals with the liquids and conditions that render foods susceptible to ritual impurity.
  • D. Ruhaya
    Ruhaya is a Bantu language spoken primarily by the Haya people of northwestern Tanzania.
  • E. Rasah
    Rasah is a residential and administrative area within the city of Seremban in the Malaysian state of Negeri Sembilan.
  • 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_69d85ccd575081908909b71a3f3e3a61 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04e47971481909e986dd999354628 completed April 16, 2026, 2:49 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff4c4f71e48190a15eb0a2138f083f completed May 9, 2026, 3:01 p.m.
Created at: April 10, 2026, 4:11 a.m.