Triple

T2659115
Position Surface form Disambiguated ID Type / Status
Subject Romeo Montague E54683 entity
Predicate loveInterest P7325 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 Montague, loveInterest, Juliet Capulet]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Juliet Capulet
Context triple: [Romeo Montague, loveInterest, 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_69ab49e028948190b97e01d73548b1d9 completed March 6, 2026, 9:40 p.m.
NER Named-entity recognition batch_69abd94dcaa48190aec625f68ce61a02 completed March 7, 2026, 7:52 a.m.
NED1 Entity disambiguation (via context triple) batch_69afaf4d70388190b6f0e683c77bc262 completed March 10, 2026, 5:42 a.m.
Created at: March 6, 2026, 9:53 p.m.