Triple

T3377164
Position Surface form Disambiguated ID Type / Status
Subject EastEnders E71091 entity
Predicate composer P1361 FINISHED
Object Simon May
Simon May is a British composer best known for creating iconic television theme tunes, including the famous theme for the soap opera EastEnders.
E353887 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: Simon May | Statement: [EastEnders, composer, Simon May]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Simon May
Context triple: [EastEnders, composer, Simon May]
  • A. Sam Mills
    Sam Mills was a standout undersized linebacker and team leader in the NFL, best known for his Pro Bowl play and inspirational presence with the New Orleans Saints and Carolina Panthers.
  • B. Stuart Maynard
    Stuart Maynard is an English football manager best known for managing Notts County F.C. in the lower tiers of the English football league system.
  • C. Suggs
    Suggs is a surname shared by various notable individuals across fields such as sports, music, and entertainment.
  • D. Jon Cornish
    Jon Cornish is a former Canadian Football League star running back who became a prominent community leader and chancellor of the University of Calgary.
  • E. Eric Blore
    Eric Blore was an English character actor best known for his comic portrayals of butlers and valets in 1930s and 1940s Hollywood films.
  • 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: Simon May
Triple: [EastEnders, composer, Simon May]
Generated description
Simon May is a British composer best known for creating iconic television theme tunes, including the famous theme for the soap opera EastEnders.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Simon May
Target entity description: Simon May is a British composer best known for creating iconic television theme tunes, including the famous theme for the soap opera EastEnders.
  • A. Sam Mills
    Sam Mills was a standout undersized linebacker and team leader in the NFL, best known for his Pro Bowl play and inspirational presence with the New Orleans Saints and Carolina Panthers.
  • B. Stuart Maynard
    Stuart Maynard is an English football manager best known for managing Notts County F.C. in the lower tiers of the English football league system.
  • C. Suggs
    Suggs is a surname shared by various notable individuals across fields such as sports, music, and entertainment.
  • D. Jon Cornish
    Jon Cornish is a former Canadian Football League star running back who became a prominent community leader and chancellor of the University of Calgary.
  • E. Eric Blore
    Eric Blore was an English character actor best known for his comic portrayals of butlers and valets in 1930s and 1940s Hollywood films.
  • 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_69ad85a7f80c8190a05e43013f298942 completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb2e8d1988190b6fb6c4c5502f25f completed March 8, 2026, 5:33 p.m.
NED1 Entity disambiguation (via context triple) batch_69b334490bf08190aa119e72d12f5e4b completed March 12, 2026, 9:46 p.m.
NEDg Description generation batch_69b334d1e3348190b231a33058ee08a5 completed March 12, 2026, 9:49 p.m.
NED2 Entity disambiguation (via description) batch_69b33901299481908615762989e45e7c completed March 12, 2026, 10:06 p.m.
Created at: March 8, 2026, 3:13 p.m.