Triple

T3067276
Position Surface form Disambiguated ID Type / Status
Subject Romeo and Juliet E62132 entity
Predicate mainCharacter P1183 FINISHED
Object Juliet Capulet E286397 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: Juliet Capulet | Statement: [Romeo and Juliet, mainCharacter, Juliet Capulet]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Juliet Capulet
Context triple: [Romeo and Juliet, mainCharacter, Juliet Capulet]
  • A. Juliet Capulet chosen
    Juliet Capulet is the young heroine of William Shakespeare’s tragedy "Romeo and Juliet," renowned as one half of literature’s most famous star-crossed lovers.
  • B. Friar Laurence
    Friar Laurence is the well-intentioned Franciscan priest in Shakespeare’s "Romeo and Juliet" who secretly marries the young lovers and devises the ill-fated plan that leads to their tragic end.
  • C. Juliette
    Juliette is a feminine given name of French origin, widely used in many countries and popularized through literature and film.
  • D. Romeo Montague
    Romeo Montague is the passionate young lover and tragic protagonist of William Shakespeare’s play "Romeo and Juliet," whose forbidden romance ends in mutual death.
  • E. Katherina
    Katherina is the given first name of Katia Mann, the wife of German novelist Thomas Mann.
  • 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_69ad85793e5c8190a358049bc4a98d8c completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ada0fea06881909e5251eea26599ac completed March 8, 2026, 4:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69b1ef16cf2881908265dfe8a1e3424d completed March 11, 2026, 10:39 p.m.
Created at: March 8, 2026, 3:02 p.m.