Triple

T22797644
Position Surface form Disambiguated ID Type / Status
Subject Konnie Huq E564292 entity
Predicate familyName P18 FINISHED
Object Huq
Huq is a surname most notably associated with British television presenter and writer Konnie Huq.
 E1555643 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: Huq | Statement: [Konnie Huq, familyName, Huq]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Huq
Context triple: [Konnie Huq, familyName, Huq]
  • A. Huwarin
    Huwarin is a town in present-day Syria historically noted as the place where the Umayyad caliph Yazid I died.
  • B. Mousa
    Mousa is a small uninhabited island in Shetland, Scotland, best known for its exceptionally well-preserved Iron Age broch, Mousa Broch.
  • C. Houjarray
    Houjarray is a small hamlet in the Île-de-France region of northern France, best known as the site of the Jean Monnet House, a key museum of European integration history.
  • D. Maharraqa
    Maharraqa was an ancient Nubian settlement in Lower Nubia, near the Nile in what is now southern Egypt or northern Sudan, notable for its archaeological remains including a Roman-period temple.
  • E. Habshan
    Habshan is a major oil and gas hub in the United Arab Emirates, known for its extensive hydrocarbon processing and production facilities.
  • 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: Huq
Triple: [Konnie Huq, familyName, Huq]
Generated description
Huq is a surname most notably associated with British television presenter and writer Konnie Huq.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Huq
Target entity description: Huq is a surname most notably associated with British television presenter and writer Konnie Huq.
  • A. Huwarin
    Huwarin is a town in present-day Syria historically noted as the place where the Umayyad caliph Yazid I died.
  • B. Mousa
    Mousa is a small uninhabited island in Shetland, Scotland, best known for its exceptionally well-preserved Iron Age broch, Mousa Broch.
  • C. Houjarray
    Houjarray is a small hamlet in the Île-de-France region of northern France, best known as the site of the Jean Monnet House, a key museum of European integration history.
  • D. Maharraqa
    Maharraqa was an ancient Nubian settlement in Lower Nubia, near the Nile in what is now southern Egypt or northern Sudan, notable for its archaeological remains including a Roman-period temple.
  • E. Habshan
    Habshan is a major oil and gas hub in the United Arab Emirates, known for its extensive hydrocarbon processing and production facilities.
  • 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_69e2458185f88190b0045227ee420411 completed April 17, 2026, 2:36 p.m.
NER Named-entity recognition batch_69f17cda76448190891c5190e1d75ae0 completed April 29, 2026, 3:36 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0b9e95a7008190860cf3aac103d07d completed May 18, 2026, 11:19 p.m.
NEDg Description generation batch_6a0ba0f5030c81909efd76deb3e6017d completed May 18, 2026, 11:29 p.m.
NED2 Entity disambiguation (via description) batch_6a0ba1b94c8081909cbd256997af1dca completed May 18, 2026, 11:33 p.m.
Created at: April 17, 2026, 3:30 p.m.