Triple

T27217897
Position Surface form Disambiguated ID Type / Status
Subject Daybreak E681188 entity
Predicate hasNewsreader P189419 FINISHED
Object Tasmin Lucia-Khan
Tasmin Lucia-Khan is a British television journalist and presenter known for her newsreading roles on UK breakfast and international news programs.
 E1759321 NE FINISHED

How this triple was built (3 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: Tasmin Lucia-Khan | Statement: [Daybreak, hasNewsreader, Tasmin Lucia-Khan]
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: Tasmin Lucia-Khan
Triple: [Daybreak, hasNewsreader, Tasmin Lucia-Khan]
Generated description
Tasmin Lucia-Khan is a British television journalist and presenter known for her newsreading roles on UK breakfast and international news programs.
PD Predicate disambiguation gpt-5-mini-2025-08-07 
Target predicate: hasNewsreader
Context triple: [Daybreak, hasNewsreader, Tasmin Lucia-Khan]
  • A. hasReading
    Indicates that an entity is associated with a particular reading, such as a measured value, interpretation, or recorded observation.
  • B. containsReading
    Indicates that one entity includes or encompasses a particular reading (such as a measurement, value, or interpretation) within it.
  • C. hasNewsPortal
    Indicates that an entity operates, maintains, or is associated with a dedicated online news portal.
  • D. hadNewspaper
    Indicates that an entity possessed or was in ownership of a newspaper at a particular time.
  • E. usesReading
    Indicates that one entity employs or relies on a particular reading (e.g., a text, measurement, or interpretation) in performing an action or fulfilling a function.
  • F. None of above. chosen

Provenance (7 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_69eefac9f64c8190a07490fe0c8b72a3 completed April 27, 2026, 5:57 a.m.
NER Named-entity recognition batch_69fbc36ce1f88190a7fa1656b714e107 completed May 6, 2026, 10:40 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1253aaf5b88190a053e3f8cb9a8881 completed May 24, 2026, 1:26 a.m.
NEDg Description generation batch_6a1254349d388190b85474fb0a86bab3 completed May 24, 2026, 1:28 a.m.
NED2 Entity disambiguation (via description) batch_6a1254fc697c8190baf4f8adefcea4d2 completed May 24, 2026, 1:31 a.m.
PD Predicate disambiguation batch_69fbbd13595c81908719f52c3d37a7e8 completed May 6, 2026, 10:13 p.m.
PDg Predicate description generation batch_69fbc36bcac48190a726b40442c094d1 completed May 6, 2026, 10:40 p.m.
Created at: April 27, 2026, 9:42 a.m.