Triple

T12809852
Position Surface form Disambiguated ID Type / Status
Subject Royal E. Ingersoll E306241 entity
Predicate givenName P17 FINISHED
Object Royal E618260 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: Royal | Statement: [Royal E. Ingersoll, givenName, Royal]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Royal
Context triple: [Royal E. Ingersoll, givenName, Royal]
  • A. Royal chosen
    Royal is a French surname most prominently associated with politician Ségolène Royal, a leading figure in contemporary French public life.
  • B. Regal
    Regal is a major American movie theater chain known for operating multiplex cinemas across the United States.
  • C. Royal Highness
    "Royal Highness" is a formal style used to address or refer to certain members of a royal family, typically princes and princesses, signifying high but not sovereign rank.
  • D. Regent
    Regent is a suburban railway station in Melbourne, Australia, serving the local community on the metropolitan train network.
  • E. Royal Crown
    Royal Crown is the original full name of the RC Cola soft drink brand, a historic American cola introduced in the early 20th century as a competitor to Coca-Cola and Pepsi.
  • 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_69d7bdf46c448190b1faa55aaacb6317 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d96e817598819080fdd61e9d61236e completed April 10, 2026, 9:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69f68ec89eb081909915af6e2216e0a2 completed May 2, 2026, 11:54 p.m.
Created at: April 9, 2026, 5:31 p.m.