Triple

T3287490
Position Surface form Disambiguated ID Type / Status
Subject Bella Swan E69017 entity
Predicate familyName P18 FINISHED
Object Swan E280999 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: Swan | Statement: [Bella Swan, familyName, Swan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Swan
Context triple: [Bella Swan, familyName, Swan]
  • A. Swan chosen
    Swan is a large, graceful waterbird known for its long neck, white or black plumage, and strong cultural associations with beauty and elegance.
  • B. Seagull
    "Seagull" is a track from Bill Callahan’s 2013 album *Dream River*, known for its atmospheric, introspective folk sound and poetic lyricism.
  • C. Swan of Lichfield
    The Swan of Lichfield is the celebrated nickname of English Romantic-era poet and letter-writer Anna Seward, renowned for her eloquent verse and influential literary salon in Lichfield.
  • D. Swallow
    Swallow is the Allied reporting name for the Japanese World War II fighter aircraft Kawasaki Ki-61, known for its inline engine and resemblance to contemporary European fighters.
  • E. Svans
    Svans are a distinct subethnic group of Georgians known for their unique Svan language, highland culture, and traditional communities in the Svaneti region of the Caucasus.
  • 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_69ad859d45748190b0742408c954b39f completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb058e00881908fdf0a23208860d4 completed March 8, 2026, 5:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69b2e85f71508190b194b4d383d7ee32 completed March 12, 2026, 4:22 p.m.
Created at: March 8, 2026, 3:10 p.m.