Triple

T2659131
Position Surface form Disambiguated ID Type / Status
Subject Romeo Montague E54683 entity
Predicate relationshipToTybalt P38921 FINISHED
Object kills Juliet’s cousin Tybalt in a duel LITERAL 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: kills Juliet’s cousin Tybalt in a duel | Statement: [Romeo Montague, relationshipToTybalt, kills Juliet’s cousin Tybalt in a duel]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: relationshipToTybalt
Context triple: [Romeo Montague, relationshipToTybalt, kills Juliet’s cousin Tybalt in a duel]
  • A. relationshipToCharacter chosen
    Indicates the specific type of personal, social, or narrative connection that one entity has to a given character.
  • B. hasProtagonistRelationship
    Indicates that there exists a central, story-driving relationship involving the protagonist and another entity within a narrative.
  • C. hasFamilialTieTo
    Indicates a relationship where two entities are connected by family bonds, such as by blood, marriage, or adoption.
  • D. fictionalRelationship
    Indicates a relationship that exists only within a fictional or imagined context between entities.
  • E. hasRomanticTensionWith
    Indicates a mutual or one-sided romantic attraction or unresolved romantic interest existing between two entities.
  • F. None of above.

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.
PD Predicate disambiguation batch_69abd81768748190bd965f367cf6ef37 completed March 7, 2026, 7:47 a.m.
Created at: March 6, 2026, 9:53 p.m.