Triple

T19412642
Position Surface form Disambiguated ID Type / Status
Subject Musa McKim E485627 entity
Predicate givenName P17 FINISHED
Object Musa
Musa is a feminine given name that has been used by various notable individuals, including the American painter and poet Musa McKim.
E1373550 NE FINISHED

How this triple was built (4 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: [Musa McKim, givenName, Musa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Musa
Context triple: [Musa McKim, givenName, Musa]
  • A. Musa
    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 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.
  • D. Musa
    Musa is a South Korean historical epic film starring Jung Woo-sung, known for its large-scale battle scenes and depiction of warriors during the Ming dynasty era.
  • E. Musa
    Musa is a studio album by Puerto Rican reggaeton artist Ivy Queen that showcases her blend of reggaeton, Latin urban, and Caribbean rhythms.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Musa
Triple: [Musa McKim, givenName, Musa]
Generated description
Musa is a feminine given name that has been used by various notable individuals, including the American painter and poet Musa McKim.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Musa
Target entity description: Musa is a feminine given name that has been used by various notable individuals, including the American painter and poet Musa McKim.
  • A. Musa
    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 was a Roman slave who became queen of the Parthian Empire and co-ruled with her son after marrying King Phraates IV.
  • D. Musa
    Musa is a genus of large herbaceous flowering plants that includes the bananas and plantains widely cultivated for their edible fruit.
  • E. Musa
    Musa is a South Korean historical epic film starring Jung Woo-sung, known for its large-scale battle scenes and depiction of warriors during the Ming dynasty era.
  • F. None of above. chosen

Provenance (5 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_69d8e8d5162481909db12435d9535c1a completed April 10, 2026, 12:11 p.m.
NER Named-entity recognition batch_69e62af77eb481909fcfb6cdde1e8580 completed April 20, 2026, 1:32 p.m.
NED1 Entity disambiguation (via context triple) batch_6a072b9a6298819097489bc8a97877c9 completed May 15, 2026, 2:20 p.m.
NEDg Description generation batch_6a072e59d3ec8190bca24039ec51a6c1 completed May 15, 2026, 2:31 p.m.
NED2 Entity disambiguation (via description) batch_6a072ec4c1988190be354a6210f2768e completed May 15, 2026, 2:33 p.m.
Created at: April 10, 2026, 1:37 p.m.