Triple

T14939302
Position Surface form Disambiguated ID Type / Status
Subject Harold Prince E372479 entity
Predicate child P120 FINISHED
Object Charles Prince E372479 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: Charles Prince | Statement: [Harold Prince, child, Charles Prince]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Charles Prince
Context triple: [Harold Prince, child, Charles Prince]
  • A. Charles Prince chosen
    Charles Prince is the son of legendary American theatre director and producer Harold Prince, known for his work as an actor and director in musical theatre.
  • B. William Prince
    William Prince was an American film, stage, and television actor active in the mid-20th century, known for his versatile character roles in Hollywood and on Broadway.
  • C. Henry Monmouth
    Henry Monmouth is the historical English prince who became King Henry V, famously depicted as Prince Hal in Shakespeare’s plays.
  • D. Prince Rupert
    Prince Rupert is a coastal city in northwestern British Columbia, Canada, known as a major deep-water port and gateway to the Inside Passage and Alaska.
  • E. Charles Pelham
    Charles Pelham is the given name of Charles Pelham Villiers, a long-serving 19th-century British Liberal politician known for his advocacy of free trade and the repeal of the Corn Laws.
  • 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_69d85cc9da0c81908d583ca3f63a3908 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69ded64a2f24819099b21566756668a2 completed April 15, 2026, 12:05 a.m.
NED1 Entity disambiguation (via context triple) batch_69fe7e9078508190b5cbfe84125ba209 completed May 9, 2026, 12:23 a.m.
Created at: April 10, 2026, 2:38 a.m.