Triple

T10364714
Position Surface form Disambiguated ID Type / Status
Subject Max Minghella E244221 entity
Predicate hasRelative P367 FINISHED
Object Hannah Minghella
Hannah Minghella is a British film executive and producer known for her leadership roles at major studios such as Sony Pictures Animation and Bad Robot.
 E858154 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: Hannah Minghella | Statement: [Max Minghella, hasRelative, Hannah Minghella]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Hannah Minghella
Context triple: [Max Minghella, hasRelative, Hannah Minghella]
  • A. Hannah Waterman
    Hannah Waterman is an English actress best known for her role as Laura Beale in the BBC soap opera EastEnders.
  • B. Lucy Benjamin
    Lucy Benjamin is a British actress best known for her long-running role as Lisa Fowler in the BBC soap opera EastEnders.
  • C. Hannah Waterman King
    Hannah Waterman King was the mother of American Revolutionary War figure Benedict Arnold and a colonial-era resident of New England.
  • D. Aanisah Hinds
    Aanisah Hinds is the daughter of American R&B and soul singer Macy Gray.
  • E. Gwendoline Horne
    Gwendoline Horne was the wife of British stage and film actor Leslie Banks, known for her marriage to the prominent performer of early 20th-century theatre and cinema.
  • 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: Hannah Minghella
Triple: [Max Minghella, hasRelative, Hannah Minghella]
Generated description
Hannah Minghella is a British film executive and producer known for her leadership roles at major studios such as Sony Pictures Animation and Bad Robot.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Hannah Minghella
Target entity description: Hannah Minghella is a British film executive and producer known for her leadership roles at major studios such as Sony Pictures Animation and Bad Robot.
  • A. Hannah Waterman
    Hannah Waterman is an English actress best known for her role as Laura Beale in the BBC soap opera EastEnders.
  • B. Lucy Benjamin
    Lucy Benjamin is a British actress best known for her long-running role as Lisa Fowler in the BBC soap opera EastEnders.
  • C. Hannah Waterman King
    Hannah Waterman King was the mother of American Revolutionary War figure Benedict Arnold and a colonial-era resident of New England.
  • D. Aanisah Hinds
    Aanisah Hinds is the daughter of American R&B and soul singer Macy Gray.
  • E. Gwendoline Horne
    Gwendoline Horne was the wife of British stage and film actor Leslie Banks, known for her marriage to the prominent performer of early 20th-century theatre and cinema.
  • 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_69d381b3e328819094b23b8edcd29b5a completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4e964a53c8190b748e80850e96656 completed April 7, 2026, 11:24 a.m.
NED1 Entity disambiguation (via context triple) batch_69d750c2d2748190b871b928d5a094f8 completed April 9, 2026, 7:09 a.m.
NEDg Description generation batch_69d7618fac288190a5da7549e5ccbdf0 completed April 9, 2026, 8:21 a.m.
NED2 Entity disambiguation (via description) batch_69d77060331c8190a773a5f9ffadf1d6 completed April 9, 2026, 9:24 a.m.
Created at: April 6, 2026, noon