Triple

T13519522
Position Surface form Disambiguated ID Type / Status
Subject Nurse (Romeo and Juliet) E322855 entity
Predicate laterAdvisesJulietToMarry P110082 FINISHED
Object Paris E107832 NE FINISHED

How this triple was built (3 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: Paris | Statement: [Nurse (Romeo and Juliet), laterAdvisesJulietToMarry, Paris]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Paris
Context triple: [Nurse (Romeo and Juliet), laterAdvisesJulietToMarry, Paris]
  • A. Paris
    Paris is the capital and largest city of France, renowned for its historic architecture, art, fashion, and cultural influence worldwide.
  • B. Paris chosen
    Paris is a prince of Troy in Greek mythology, best known for judging the beauty contest of the goddesses and for abducting Helen, which sparked the Trojan War.
  • C. Paris
    Paris is a major Chilean department store and retail chain offering a wide range of apparel, home goods, and consumer products.
  • D. Paris
    Paris is a budget-oriented AMD Sempron processor core designed for entry-level desktop computing.
  • E. Paris
    "Paris" is a 2017 electronic dance music single by The Chainsmokers that became a major international hit.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: laterAdvisesJulietToMarry
Context triple: [Nurse (Romeo and Juliet), laterAdvisesJulietToMarry, Paris]
  • A. proposesMarriageAs
    Indicates that one entity formally asks another entity to enter into a marital relationship.
  • B. asksToMarry
    Indicates that one entity proposes marriage to another, requesting that they become spouses.
  • C. rivalForMarriageOf
    Indicates that one entity is a romantic competitor with another entity for the opportunity to marry a specific third entity.
  • D. arrangedMarriageFor
    Indicates that one entity has organized or set up a marriage for another entity.
  • E. attemptedMarriage
    Indicates that one entity tried or intended to enter into a marital relationship with another entity, regardless of whether the marriage was completed or legally recognized.
  • 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_69d80766a21881909f21a1b7421d3b8a completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbafa27f048190bed33a98e28c8d09 completed April 12, 2026, 2:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7547d4f20819096765e125396e471 completed May 3, 2026, 1:58 p.m.
PD Predicate disambiguation batch_69dbae0b63748190b5e207f84b2532ea completed April 12, 2026, 2:36 p.m.
PDg Predicate description generation batch_69dbaee128d88190b097be17fdd2f92b completed April 12, 2026, 2:40 p.m.
Created at: April 9, 2026, 9:44 p.m.