Triple

T2739585
Position Surface form Disambiguated ID Type / Status
Subject Isabella II of Spain E60716 entity
Predicate givenName P17 FINISHED
Object Isabella E114378 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: Isabella | Statement: [Isabella II of Spain, givenName, Isabella]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Isabella
Context triple: [Isabella II of Spain, givenName, Isabella]
  • A. Isabella
    Isabella is a virtuous and resourceful young noblewoman in Horace Walpole’s Gothic novel "The Castle of Otranto," whose peril and resistance drive much of the story’s suspense and drama.
  • B. Isabel chosen
    Isabel is a feminine given name of Spanish origin, widely used in Spanish- and Portuguese-speaking countries and borne by numerous notable historical and contemporary figures.
  • C. Katherine
    Katherine is a regional town in Australia's Northern Territory, known as a key service and transport hub near Nitmiluk (Katherine Gorge) National Park.
  • D. Beatrix
    Beatrix is the former Queen of the Netherlands who reigned from 1980 until her abdication in 2013.
  • E. Beatrix
    Beatrix is the first name of the beloved English author and illustrator Beatrix Potter, famed for creating classic children's tales such as "The Tale of Peter Rabbit."
  • 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_69ab4b77febc819095603eb012cd141b completed March 6, 2026, 9:47 p.m.
NER Named-entity recognition batch_69abdb2da94c8190bc9d23262e3dfc07 completed March 7, 2026, 8 a.m.
NED1 Entity disambiguation (via context triple) batch_69afc640af508190b5d089dc5feac504 completed March 10, 2026, 7:20 a.m.
Created at: March 6, 2026, 9:56 p.m.