Triple

T16798736
Position Surface form Disambiguated ID Type / Status
Subject Lally Weymouth E408298 entity
Predicate spouse P13 FINISHED
Object Yann Weymouth E226787 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: Yann Weymouth | Statement: [Lally Weymouth, spouse, Yann Weymouth]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Yann Weymouth
Context triple: [Lally Weymouth, spouse, Yann Weymouth]
  • A. Yann Weymouth chosen
    Yann Weymouth is an American architect known for designing prominent cultural and museum buildings, including the Salvador Dalí Museum in St. Petersburg, Florida.
  • B. Yann
    Yann is the given name of Yann LeCun, a pioneering computer scientist known for his foundational work in deep learning and convolutional neural networks.
  • C. Hudson Fysh
    Hudson Fysh was an Australian aviator and businessman best known as a co-founder and long-serving leader of Qantas, helping to establish it as a major international airline.
  • D. Sebastian Oldsmith
    Sebastian Oldsmith is the central protagonist of the novel "Shout at the Devil," around whom the story’s main events and conflicts revolve.
  • E. Sebastian Wilder
    Sebastian Wilder is a passionate jazz pianist and aspiring club owner in the film "La La Land," whose romance and artistic ambitions drive much of the movie’s emotional core.
  • 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_69d88393905081908d00a86b99996ac8 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e3b2abc430819080c1303eded5f416 completed April 18, 2026, 4:34 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00ab1299ac81908e9f1eebc3424bb9 completed May 10, 2026, 3:58 p.m.
Created at: April 10, 2026, 5:22 a.m.