Triple

T12884841
Position Surface form Disambiguated ID Type / Status
Subject Maggie Tulliver E308198 entity
Predicate hasLoveInterest P7325 FINISHED
Object Stephen Guest E308193 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: Stephen Guest | Statement: [Maggie Tulliver, hasLoveInterest, Stephen Guest]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Stephen Guest
Context triple: [Maggie Tulliver, hasLoveInterest, Stephen Guest]
  • A. Stephen Guest chosen
    Stephen Guest is a charming yet morally conflicted young man in George Eliot’s novel "The Mill on the Floss," whose romantic entanglement with Maggie Tulliver drives much of the story’s emotional tension.
  • B. Nicholas Guest
    Nicholas Guest is an American character actor known for his extensive work in film, television, and voice acting since the late 1970s.
  • C. Christopher Belling
    Christopher Belling is a flamboyant, sharp-tongued English director character in the musical comedy whodunit "Curtains."
  • D. Graham Hess
    Graham Hess is a former Episcopal priest and widowed father who struggles with his faith while protecting his family during a mysterious alien invasion in the film "Signs."
  • E. Tom Goodman-Hill
    Tom Goodman-Hill is a British actor known for his work in television, film, and theatre, including roles in series such as "Humans" and "Mr Selfridge."
  • 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_69d7bdf7c1f0819098102569a8d8cbf5 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d9714208f881908f7f8a921362909a completed April 10, 2026, 9:53 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6cbbb199081909c32575097fbc2bf completed May 3, 2026, 4:14 a.m.
Created at: April 9, 2026, 5:39 p.m.