Triple

T20853857
Position Surface form Disambiguated ID Type / Status
Subject Muhammad ibn Danishmend E513428 entity
Predicate hasGivenName P17 FINISHED
Object Muhammad 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: Muhammad | Statement: [Muhammad ibn Danishmend, hasGivenName, Muhammad]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Muhammad
Context triple: [Muhammad ibn Danishmend, hasGivenName, Muhammad]
  • A. Muhammad
    Muhammad is the 7th-century Arab religious, political, and social leader regarded by Muslims as the final prophet and messenger of God in Islam.
  • B. Muhammad ibn al-Hanafiyyah
    Muhammad ibn al-Hanafiyyah was a prominent early Islamic figure and son of Ali ibn Abi Talib, known for his piety, scholarship, and role in the political and theological developments following the early caliphates.
  • C. Mohammad
    Mohammad is the given first name of Indonesian independence leader and former vice president Bung Hatta.
  • D. Mohammad chosen
    Mohammad is a common Arabic male given name, most notably borne by the Prophet of Islam and widely used across the Muslim world.
  • E. Abu Hafs al-Hashimi al-Qurashi
    Abu Hafs al-Hashimi al-Qurashi is a senior jihadist militant who has been identified as a leader within the Islamic State organization.
  • 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_69e0b4f5b01081909452f654d2fc3f50 completed April 16, 2026, 10:07 a.m.
NER Named-entity recognition batch_69e6c3a6015081909f604a88d04b36ea completed April 21, 2026, 12:24 a.m.
Created at: April 16, 2026, 12:44 p.m.