Triple

T9114745
Position Surface form Disambiguated ID Type / Status
Subject Dormammu E218694 entity
Predicate family P566 FINISHED
Object Umar E800478 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: Umar | Statement: [Dormammu, family, Umar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Umar
Context triple: [Dormammu, family, Umar]
  • A. Umar chosen
    Umar is a powerful extra-dimensional sorcerer and recurring antagonist in Marvel Comics, often associated with the Dark Dimension and the character Clea.
  • B. Umar ibn Abi Salama
    Umar ibn Abi Salama was a young Companion of the Prophet Muhammad and the stepson of the Prophet through his mother, Umm Salama.
  • C. Umar ibn al-Khattab
    Umar ibn al-Khattab was the second caliph of Islam and a close companion of the Prophet Muhammad, renowned for his just governance and major role in the early expansion of the Muslim state.
  • D. Umar ibn Saʿd
    Umar ibn Saʿd was an Umayyad military leader best known for leading the forces that killed Husayn ibn Ali at the Battle of Karbala in 680 CE.
  • E. Abu Umar
    Abu Umar is the honorific kunya of the renowned Andalusian Maliki scholar and hadith expert Ibn Abd al-Barr.
  • 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_69ca83dc94ac8190b9ef42684d36ff39 completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69cca84c209c8190b082a9b8499bedf7 completed April 1, 2026, 5:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69d139a887b0819088485006f1653d1c completed April 4, 2026, 4:17 p.m.
Created at: March 30, 2026, 7:16 p.m.