Triple

T21921659
Position Surface form Disambiguated ID Type / Status
Subject Aladdin (TV series) E541329 entity
Predicate recurringCharacter P12208 FINISHED
Object Rajah 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: Rajah | Statement: [Aladdin (TV series), recurringCharacter, Rajah]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rajah
Context triple: [Aladdin (TV series), recurringCharacter, Rajah]
  • A. Rajah chosen
    Rajah is the loyal and protective tiger companion of Princess Jasmine in Disney's Aladdin franchise.
  • B. Raja
    Raja is a traditional Indian royal title historically used by Hindu monarchs and regional rulers.
  • C. Rajah Buayan
    Rajah Buayan is a municipality in the province of Maguindanao in the Philippines, known for its predominantly Muslim population and location in the Bangsamoro Autonomous Region in Muslim Mindanao.
  • D. Tuan Besar
    Tuan Besar was a Malay honorific title denoting the ruling White Rajah of Sarawak, signifying his status as the paramount leader.
  • E. Rajam
    Rajam was the wife of celebrated Indian novelist R. K. Narayan, remembered for her brief but deeply influential marriage that shaped much of his emotional and literary life.
  • 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_69e0c47d74488190a15119108794a307 completed April 16, 2026, 11:14 a.m.
NER Named-entity recognition batch_69f1233c29008190b84ae551b14eb2db completed April 28, 2026, 9:14 p.m.
Created at: April 16, 2026, 7:45 p.m.