Triple

T2130963
Position Surface form Disambiguated ID Type / Status
Subject Sylvia Hall E46536 entity
Predicate familyName P18 FINISHED
Object Hall E141105 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: Hall | Statement: [Sylvia Hall, familyName, Hall]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hall
Context triple: [Sylvia Hall, familyName, Hall]
  • A. Hall chosen
    Hall is a common English surname borne by numerous notable individuals across diverse fields such as science, arts, and public life.
  • B. Hall 2
    Hall 2 is one of the main concourse areas within Paris’s Gare de Lyon railway station, serving passengers with platforms, services, and amenities.
  • C. Hall 1
    Hall 1 is one of the main passenger halls of Paris’s Gare de Lyon railway station, serving as a central area for platforms, services, and traveler amenities.
  • D. The Academy
    The Academy is a prominent American professional organization of musicians, producers, and recording professionals best known for presenting the annual Grammy Awards.
  • E. Hallidie
    Hallidie is a surname most notably associated with Andrew Smith Hallidie, the 19th-century engineer credited with pioneering San Francisco’s cable car system.
  • 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_69a88a1626548190ae59a5028c3baa8e completed March 4, 2026, 7:37 p.m.
NER Named-entity recognition batch_69abbb79f21881909ad8d1a09c1f29fd completed March 7, 2026, 5:45 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae51a5d95881909b4b77c14f565e21 completed March 9, 2026, 4:50 a.m.
Created at: March 4, 2026, 7:44 p.m.