Triple

T13541015
Position Surface form Disambiguated ID Type / Status
Subject Hillary Whitney E323384 entity
Predicate diesIn P21 FINISHED
Object Beaches E60486 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: Beaches | Statement: [Hillary Whitney, diesIn, Beaches]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Beaches
Context triple: [Hillary Whitney, diesIn, Beaches]
  • A. Beaches chosen
    Beaches is a 1988 American drama film starring Bette Midler that follows the lifelong friendship between two very different women.
  • B. Beach
    Beach is a common English surname borne by various notable individuals across politics, journalism, and the arts.
  • C. Beach
    Beach is the long-suffering butler in P. G. Wodehouse’s Blandings Castle stories, known for his dignified composure amid the eccentric chaos of the castle’s inhabitants.
  • D. Tunnels Beaches
    Tunnels Beaches is a historic network of hand-carved tunnels leading to sheltered tidal bathing pools and a beach in Ilfracombe, North Devon, England.
  • E. Sand Beach
    Sand Beach is a small, picturesque sandy shoreline on Mount Desert Island in Maine, known for its cold waters, dramatic rocky surroundings, and popularity with visitors to Acadia National Park.
  • 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_69d8076776248190bdf0d4fa1f85a5fc completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbafd8ba10819098faadcc6adf251e completed April 12, 2026, 2:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7c6f931048190ad5182a8c2ebecb6 completed May 3, 2026, 10:06 p.m.
Created at: April 9, 2026, 9:45 p.m.