Triple

T3955960
Position Surface form Disambiguated ID Type / Status
Subject Hamlet (stage performances) E84977 entity
Predicate hasCharacter P2308 FINISHED
Object Gertrude E187883 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: Gertrude | Statement: [Hamlet (stage performances), hasCharacter, Gertrude]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gertrude
Context triple: [Hamlet (stage performances), hasCharacter, Gertrude]
  • A. Gertrude chosen
    Gertrude is a feminine given name of Germanic origin, historically popular in Europe and North America.
  • B. Gertrude of Hohenberg
    Gertrude of Hohenberg was a 13th-century German noblewoman who became Queen consort of Germany as the first wife of King Rudolf I of Habsburg.
  • C. Ophelia
    Ophelia is a famous 1894 Pre-Raphaelite painting by John William Waterhouse depicting the tragic Shakespearean heroine from Hamlet.
  • D. Ophelia
    Ophelia is a famous 1851–52 painting by John Everett Millais, emblematic of the Pre-Raphaelite movement and depicting Shakespeare’s tragic heroine floating in a stream surrounded by lush, detailed flora.
  • E. Ophelia
    Ophelia is a savvy and resourceful sex worker in the 1983 comedy film "Trading Places," who helps the protagonist navigate his sudden reversal of fortune.
  • 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_69aed934fbfc8190847068e4546de963 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aef93f3ad48190b96b98b4aecd6030 completed March 9, 2026, 4:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69b533aea08c8190b83d83e3ba89848c completed March 14, 2026, 10:08 a.m.
Created at: March 9, 2026, 3:30 p.m.