Triple

T15850218
Position Surface form Disambiguated ID Type / Status
Subject Kalim Allah E384314 entity
Predicate associatedWith P37 FINISHED
Object Musa E81197 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: Musa | Statement: [Kalim Allah, associatedWith, Musa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Musa
Context triple: [Kalim Allah, associatedWith, Musa]
  • A. Musa chosen
    Musa is the name used in the Quran for the prophet Moses, a central figure in Islamic tradition known for leading the Israelites and receiving divine revelation.
  • B. Musa
    Musa is a central character in Arundhati Roy’s novel "The Ministry of Utmost Happiness," around whom key political and personal conflicts in Kashmir revolve.
  • C. Musa
    Musa is a genus of large herbaceous flowering plants that includes the bananas and plantains widely cultivated for their edible fruit.
  • D. Musa
    Musa is a central character in the documentary film "The Bengal Tiger at the Baghdad Zoo," which follows the experiences of Iraqis and American soldiers amid the chaos of post-invasion Baghdad.
  • E. Musa
    Musa was a Roman slave who became queen of the Parthian Empire and co-ruled with her son after marrying King Phraates IV.
  • 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_69d86da422088190aac39e32e6c68429 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e14cab0fe48190bd6629e071761e91 completed April 16, 2026, 8:55 p.m.
NED1 Entity disambiguation (via context triple) batch_69ffb03c8cb081908c18c7b2d143c4b4 completed May 9, 2026, 10:07 p.m.
Created at: April 10, 2026, 4:50 a.m.