Triple

T1533576
Position Surface form Disambiguated ID Type / Status
Subject Ruqayyah bint Muhammad E32499 entity
Predicate ethnicity P194 FINISHED
Object Arab E5830 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: Arab | Statement: [Ruqayyah bint Muhammad, ethnicity, Arab]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Arab
Context triple: [Ruqayyah bint Muhammad, ethnicity, Arab]
  • A. Arabs chosen
    Arabs are a diverse ethnolinguistic group originating from the Arabian Peninsula and surrounding regions, united primarily by the Arabic language and a shared cultural and historical heritage.
  • B. Arab world
    The Arab world is a culturally and linguistically connected region of Arabic-speaking countries spanning North Africa and Western Asia.
  • C. Arabic
    Arabic is a Semitic language widely spoken across the Arab world and used as a liturgical language in Islam.
  • D. Hijazi Arabic
    Hijazi Arabic is a major regional variety of Arabic spoken primarily in western Saudi Arabia, especially in the Hijaz region including cities like Mecca, Medina, and Jeddah.
  • E. Levantine Arabic
    Levantine Arabic is a major colloquial variety of Arabic spoken primarily in the Eastern Mediterranean region, including countries such as Lebanon, Syria, Jordan, and Palestine.
  • 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_69a885ea86308190998f6bc14bb91f8e completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69aa61f8df00819086f34847e2170e12 completed March 6, 2026, 5:11 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad295a03d881909071fb437c2d19ba completed March 8, 2026, 7:46 a.m.
Created at: March 4, 2026, 7:26 p.m.