Triple

T588476
Position Surface form Disambiguated ID Type / Status
Subject The Narrows E17212 entity
Predicate near P350 FINISHED
Object St. George E33080 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: St. George | Statement: [The Narrows, near, St. George]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: St. George
Context triple: [The Narrows, near, St. George]
  • A. St. George chosen
    St. George is a waterfront neighborhood on the northeastern tip of Staten Island in New York City, known for its ferry terminal, civic buildings, and views of the Manhattan skyline.
  • B. St George
    St George is a Christian martyr and legendary dragon-slaying warrior venerated as a patron saint of England and chivalry.
  • C. Saint George of Lydda
    Saint George of Lydda is a Christian martyr and legendary soldier-saint, best known as the dragon-slaying patron saint of England and various other regions.
  • D. Geoffrey
    Geoffrey is a masculine given name of English origin, famously borne by pioneering computer scientist and AI researcher Geoffrey Hinton.
  • E. Saint George and the Dragon
    Saint George and the Dragon is a legendary Christian tale and iconic motif depicting Saint George heroically slaying a dragon, symbolizing the triumph of good over evil.
  • 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_69a49379d09c8190ac7e00b24e2810b1 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a49b9d1e68819096a9b5e7b2e83d6e completed March 1, 2026, 8:03 p.m.
NED1 Entity disambiguation (via context triple) batch_69a5103be4b881908fcd20c4c781c0a0 completed March 2, 2026, 4:21 a.m.
Created at: March 1, 2026, 7:33 p.m.