Triple

T9465643
Position Surface form Disambiguated ID Type / Status
Subject Liverpool Institute E228262 entity
Predicate notableAlumnus P304 FINISHED
Object Peter Sissons E274301 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: Peter Sissons | Statement: [Liverpool Institute, notableAlumnus, Peter Sissons]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Peter Sissons
Context triple: [Liverpool Institute, notableAlumnus, Peter Sissons]
  • A. Peter Sissons chosen
    Peter Sissons was a prominent British journalist and television newsreader best known for presenting major news programmes on the BBC and ITN.
  • B. Greg Mathieson
    Greg Mathieson is an American keyboardist, composer, and producer known for his work in jazz, fusion, and pop music, collaborating with numerous prominent artists.
  • C. Stephen Pycroft
    Stephen Pycroft is a British businessman best known as the founder of the construction and consultancy company Mace Group.
  • D. Pete Solley
    Pete Solley is an English musician, producer, and keyboardist best known for his work with rock bands such as Procol Harum and his extensive career as a record producer.
  • E. Stephen Enniss
    Stephen Enniss is an American librarian and scholar of literary archives who leads the Harry Ransom Center at the University of Texas at Austin.
  • 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_69ca846fee388190a6ec273fd644b88b completed March 30, 2026, 2:10 p.m.
NER Named-entity recognition batch_69cd7fdad3c4819083b06f1b45acc85a completed April 1, 2026, 8:28 p.m.
NED1 Entity disambiguation (via context triple) batch_69d189e601508190b116fca9854057bc completed April 4, 2026, 10 p.m.
Created at: March 30, 2026, 7:53 p.m.