Triple

T14944864
Position Surface form Disambiguated ID Type / Status
Subject Green Wing E372630 entity
Predicate producer P490 FINISHED
Object Victoria Pile E1231664 NE FINISHED

How this triple was built (2 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: Victoria Pile | Statement: [Green Wing, producer, Victoria Pile]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Victoria Pile
Context triple: [Green Wing, producer, Victoria Pile]
  • A. Victoria Pile chosen
    Victoria Pile is a British television writer, director, and producer best known for creating the surreal hospital sitcom "Green Wing."
  • B. Helen Dawes
    Helen Dawes is a key supporting character in the period drama film "Albert Nobbs," involved in the emotional and social complexities surrounding the title character's secret life.
  • C. Sarah Angliss
    Sarah Angliss is a British composer, multi-instrumentalist, and sound artist known for blending electronics, robotics, and early music influences in her experimental works.
  • D. Mary Pugh
    Mary Pugh is a notable individual distinguished enough to be recognized as a prominent bearer of the surname Pugh.
  • E. Marjorie Parry
    Marjorie Parry was the wife of renowned English conductor and cellist Sir John Barbirolli.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69d85cc9da0c81908d583ca3f63a3908 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69ded68d20048190a403af85fe43dede completed April 15, 2026, 12:06 a.m.
NED1 Entity disambiguation (via context triple) batch_6a00b272ea6c8190b22fd78081446701 completed May 10, 2026, 4:29 p.m.
Created at: April 10, 2026, 2:39 a.m.