Triple

T1234480
Position Surface form Disambiguated ID Type / Status
Subject Wendy Hall E26515 entity
Predicate familyName P18 FINISHED
Object Hall
Hall is a common English surname borne by numerous notable individuals across diverse fields such as science, arts, and public life.
 E141105 NE FINISHED

How this triple was built (4 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: [Wendy Hall, familyName, Hall]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Hall
Context triple: [Wendy Hall, familyName, Hall]
  • A. 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.
  • B. 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.
  • C. The Academy
    The Academy is a prominent American professional organization of musicians, producers, and recording professionals best known for presenting the annual Grammy Awards.
  • D. 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.
  • E. Hall of Names
    The Hall of Names is a memorial and archival space at Yad Vashem in Jerusalem dedicated to preserving the names and personal details of Jewish Holocaust victims.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Hall
Triple: [Wendy Hall, familyName, Hall]
Generated description
Hall is a common English surname borne by numerous notable individuals across diverse fields such as science, arts, and public life.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Hall
Target entity description: Hall is a common English surname borne by numerous notable individuals across diverse fields such as science, arts, and public life.
  • A. 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.
  • B. 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.
  • C. The Academy
    The Academy is a prominent American professional organization of musicians, producers, and recording professionals best known for presenting the annual Grammy Awards.
  • D. 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.
  • E. Hall of Names
    The Hall of Names is a memorial and archival space at Yad Vashem in Jerusalem dedicated to preserving the names and personal details of Jewish Holocaust victims.
  • F. None of above. chosen

Provenance (5 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_69a4948571c88190a9191e451e6035fd completed March 1, 2026, 7:33 p.m.
NER Named-entity recognition batch_69a4be5e421081908f2432528019db25 completed March 1, 2026, 10:31 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac8a16badc8190b5b603db0ca738cb completed March 7, 2026, 8:27 p.m.
NEDg Description generation batch_69ac8b70bd888190bed944579237bfad completed March 7, 2026, 8:32 p.m.
NED2 Entity disambiguation (via description) batch_69ac8bce4be48190b7e396d31e881450 completed March 7, 2026, 8:34 p.m.
Created at: March 1, 2026, 7:47 p.m.