Triple

T13581093
Position Surface form Disambiguated ID Type / Status
Subject Lord Capulet E324417 entity
Predicate promisesMarriage P110153 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: [Lord Capulet, promisesMarriage, Paris]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Paris
Context triple: [Lord Capulet, promisesMarriage, 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 budget-oriented AMD Sempron processor core designed for entry-level desktop computing.
  • D. Paris
    Paris is a major Chilean department store and retail chain offering a wide range of apparel, home goods, and consumer products.
  • 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: promisesMarriage
Context triple: [Lord Capulet, promisesMarriage, Paris]
  • A. promises
    Indicates that one entity commits to performing, providing, or ensuring something for another entity in the future.
  • B. marriesFor
    Indicates that one entity enters into marriage with another entity specifically for a particular reason, motive, or benefit.
  • C. marries
    Indicates that one entity enters into a legally or socially recognized marital union with another entity.
  • D. asksToMarry
    Indicates that one entity proposes marriage to another, requesting that they become spouses.
  • E. marriageResolvedBy
    Indicates that a marital relationship between two parties has been formally concluded or dissolved through a specific resolving action or process (e.g., divorce, annulment).
  • 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_69d80769100c819099111274614f5ed2 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbb03052088190a2b68c106059828e completed April 12, 2026, 2:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69f77f7fcab0819091146d54d56f08d7 completed May 3, 2026, 5:01 p.m.
PD Predicate disambiguation batch_69dbae161a0481909f9d3f40ca4e0ac5 completed April 12, 2026, 2:37 p.m.
PDg Predicate description generation batch_69dbaf7fefa881908471f1400f813ccc completed April 12, 2026, 2:43 p.m.
Created at: April 9, 2026, 9:48 p.m.