Triple

T11369362
Position Surface form Disambiguated ID Type / Status
Subject Charlotte Coleman E269300 entity
Predicate name P16 FINISHED
Object Charlotte Coleman E269300 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: Charlotte Coleman | Statement: [Charlotte Coleman, name, Charlotte Coleman]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Charlotte Coleman
Context triple: [Charlotte Coleman, name, Charlotte Coleman]
  • A. Charlotte Coleman chosen
    Charlotte Coleman was a British actress best known for her role as Scarlett in the romantic comedy film "Four Weddings and a Funeral."
  • B. Ann Coleman
    Ann Coleman was a key benefactor and restorer of France’s Château de Villandry, helping to preserve and revive the historic Renaissance estate and its renowned gardens.
  • C. Anna Coleman
    Anna Coleman is the rebellious teenage daughter who swaps bodies with her strict mother in the 2003 fantasy-comedy film "Freaky Friday."
  • D. Mary Cunningham
    Mary Cunningham is known as the spouse of Welsh actor Clive Merrison, recognized for his extensive work in British television, film, and radio drama.
  • E. Lisa Coleman
    Lisa Coleman is an American musician and composer best known as a member of Prince’s backing band The Revolution and for her extensive film and television scoring work.
  • 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_69d6aacca1048190b39dbbc2174616fa completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7ea89e1148190b0ca29db9d7e2cbd completed April 9, 2026, 6:06 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6b8b5ad3c81909c38c83804b7d337 completed May 3, 2026, 2:53 a.m.
Created at: April 8, 2026, 9:33 p.m.