Triple

T15359560
Position Surface form Disambiguated ID Type / Status
Subject Mika Miko E367253 entity
Predicate member P10 FINISHED
Object Kate Hall
Kate Hall is an American musician best known as a member of the Los Angeles-based punk band Mika Miko.
E1164795 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: Kate Hall | Statement: [Mika Miko, member, Kate Hall]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kate Hall
Context triple: [Mika Miko, member, Kate Hall]
  • A. Kate Harrington
    Kate Harrington is known as the former spouse of American film director John McTiernan, who is famous for action films such as "Die Hard" and "Predator."
  • B. Jewel Staite
    Jewel Staite is a Canadian actress best known for her role as Kaylee Frye in the TV series "Firefly" and its film continuation "Serenity."
  • C. Daniela Denby-Ashe
    Daniela Denby-Ashe is a British actress best known for her roles in television series such as "My Family," "EastEnders," and the period drama "North & South."
  • D. Laura Hunt
    Laura Hunt is the enigmatic advertising executive at the center of the classic 1944 film noir "Laura," whose apparent murder and idealized image drive the film’s mystery and romantic obsession.
  • E. Kathryn Price
    Kathryn Price is a screenwriter best known for co-writing the family sports comedy film "The Game Plan."
  • 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: Kate Hall
Triple: [Mika Miko, member, Kate Hall]
Generated description
Kate Hall is an American musician best known as a member of the Los Angeles-based punk band Mika Miko.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Kate Hall
Target entity description: Kate Hall is an American musician best known as a member of the Los Angeles-based punk band Mika Miko.
  • A. Kate Harrington
    Kate Harrington is known as the former spouse of American film director John McTiernan, who is famous for action films such as "Die Hard" and "Predator."
  • B. Jewel Staite
    Jewel Staite is a Canadian actress best known for her role as Kaylee Frye in the TV series "Firefly" and its film continuation "Serenity."
  • C. Daniela Denby-Ashe
    Daniela Denby-Ashe is a British actress best known for her roles in television series such as "My Family," "EastEnders," and the period drama "North & South."
  • D. Laura Hunt
    Laura Hunt is the enigmatic advertising executive at the center of the classic 1944 film noir "Laura," whose apparent murder and idealized image drive the film’s mystery and romantic obsession.
  • E. Kathryn Price
    Kathryn Price is a screenwriter best known for co-writing the family sports comedy film "The Game Plan."
  • 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_69d85a1483788190ad93c2748e8af34b completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e03e4607408190ab281a7f7a8012d3 completed April 16, 2026, 1:41 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff4c2efb148190a2e6c0811f2afb5f completed May 9, 2026, 3:01 p.m.
NEDg Description generation batch_69ff4d4dd8108190aa3271a9feaea5ca completed May 9, 2026, 3:05 p.m.
NED2 Entity disambiguation (via description) batch_69ff4e29e8a48190bf7728cf2d099a7e completed May 9, 2026, 3:09 p.m.
Created at: April 10, 2026, 3:18 a.m.