Triple

T13672493
Position Surface form Disambiguated ID Type / Status
Subject Omah Lay E327783 entity
Predicate notableWork P4 FINISHED
Object Pami
"Pami" is a popular Afrobeats song by Nigerian singer Omah Lay, known for its smooth melodies and romantic, laid-back vibe.
 E1053089 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: Pami | Statement: [Omah Lay, notableWork, Pami]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Pami
Context triple: [Omah Lay, notableWork, Pami]
  • A. Pami
    Pami was a pharaoh of Egypt’s Twenty-second Dynasty, a Libyan-origin ruler known from the Third Intermediate Period.
  • B. Moravec
    Moravec is a Czech surname most notably associated with figures such as mountaineer Fritz Moravec and roboticist Hans Moravec.
  • C. Thrun
    Thrun is the surname of Sebastian Thrun, a prominent computer scientist and robotics expert known for his work in self-driving cars and artificial intelligence.
  • D. Kismet
    Kismet is a 1955 MGM musical fantasy film directed by Vincente Minnelli, adapted from the Broadway musical set in a stylized, exoticized Baghdad.
  • E. Kismet
    Kismet is an open-source wireless network detector, sniffer, and intrusion detection system widely used for Wi-Fi security auditing and monitoring.
  • 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: Pami
Triple: [Omah Lay, notableWork, Pami]
Generated description
"Pami" is a popular Afrobeats song by Nigerian singer Omah Lay, known for its smooth melodies and romantic, laid-back vibe.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Pami
Target entity description: "Pami" is a popular Afrobeats song by Nigerian singer Omah Lay, known for its smooth melodies and romantic, laid-back vibe.
  • A. Pami
    Pami was a pharaoh of Egypt’s Twenty-second Dynasty, a Libyan-origin ruler known from the Third Intermediate Period.
  • B. Moravec
    Moravec is a Czech surname most notably associated with figures such as mountaineer Fritz Moravec and roboticist Hans Moravec.
  • C. Thrun
    Thrun is the surname of Sebastian Thrun, a prominent computer scientist and robotics expert known for his work in self-driving cars and artificial intelligence.
  • D. Kismet
    Kismet is a 1955 MGM musical fantasy film directed by Vincente Minnelli, adapted from the Broadway musical set in a stylized, exoticized Baghdad.
  • E. Kismet
    Kismet is a small, laid-back beach community on Fire Island, New York, known for its vacation homes, bars, and easygoing summer atmosphere.
  • 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_69d8076f1fa8819094664a59b55010df completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbc65aab348190a6611f5765f8392d completed April 12, 2026, 4:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69f78b1222648190a70f50e6e5c34593 completed May 3, 2026, 5:51 p.m.
NEDg Description generation batch_69f78c0030e481909c20f21ddaa480dc completed May 3, 2026, 5:55 p.m.
NED2 Entity disambiguation (via description) batch_69f78d6d74bc8190ad5476a06e8fd8ad completed May 3, 2026, 6:01 p.m.
Created at: April 9, 2026, 9:53 p.m.