Triple

T17878156
Position Surface form Disambiguated ID Type / Status
Subject Sophie Ellis-Bextor E447010 entity
Predicate album P1995 FINISHED
Object Hana
Hana is a studio album by English singer-songwriter Sophie Ellis-Bextor that showcases her blend of dance-pop and introspective, melodic songwriting.
 E1299915 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: Hana | Statement: [Sophie Ellis-Bextor, album, Hana]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Hana
Context triple: [Sophie Ellis-Bextor, album, Hana]
  • A. Hana
    Hana is a person known primarily as the romantic partner of Kip.
  • B. Hana
    Hana is a small, remote town on the eastern coast of Maui, Hawaii, known for its lush landscapes, waterfalls, and the scenic Road to Hana.
  • C. Hana
    Hana is a common female given name of Hebrew origin, often associated with meanings like "grace" or "favor."
  • D. Hana
    Hana is a Japanese restaurant located within Tokyo Disney Resort’s Disney Ambassador Hotel, offering themed dining to hotel guests and park visitors.
  • E. Hana
    Hana is a compassionate Canadian army nurse in Michael Ondaatje's novel "The English Patient," who cares for a badly burned man in an abandoned Italian villa during World War II.
  • 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: Hana
Triple: [Sophie Ellis-Bextor, album, Hana]
Generated description
Hana is a studio album by English singer-songwriter Sophie Ellis-Bextor that showcases her blend of dance-pop and introspective, melodic songwriting.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Hana
Target entity description: Hana is a studio album by English singer-songwriter Sophie Ellis-Bextor that showcases her blend of dance-pop and introspective, melodic songwriting.
  • A. Hana
    Hana is a compassionate Canadian army nurse in Michael Ondaatje's novel "The English Patient," who cares for a badly burned man in an abandoned Italian villa during World War II.
  • B. Hana
    Hana is a small, remote town on the eastern coast of Maui, Hawaii, known for its lush landscapes, waterfalls, and the scenic Road to Hana.
  • C. Hana
    Hana is a person known primarily as the romantic partner of Kip.
  • D. Hana
    Hana is a common female given name of Hebrew origin, often associated with meanings like "grace" or "favor."
  • E. Hana
    Hana is a Japanese restaurant located within Tokyo Disney Resort’s Disney Ambassador Hotel, offering themed dining to hotel guests and park visitors.
  • 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_69d8b9f4c22c819093c2680434472894 completed April 10, 2026, 8:51 a.m.
NER Named-entity recognition batch_69e49c0c46108190b8edef2572b5ba90 completed April 19, 2026, 9:10 a.m.
NED1 Entity disambiguation (via context triple) batch_6a03379bd8d08190b46a72df4502d95c completed May 12, 2026, 2:22 p.m.
NEDg Description generation batch_6a033ca5e4c08190b7de8ab2d4fb8e3b completed May 12, 2026, 2:43 p.m.
NED2 Entity disambiguation (via description) batch_6a033daf5b948190926f2925b8e3cc84 completed May 12, 2026, 2:48 p.m.
Created at: April 10, 2026, 10:18 a.m.