Triple

T819253
Position Surface form Disambiguated ID Type / Status
Subject South Hall E17715 entity
Predicate neighboringBuilding P231 FINISHED
Object North Hall (demolished)
North Hall (demolished) was a former campus building that once stood adjacent to South Hall before being torn down.
 E98314 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: North Hall (demolished) | Statement: [South Hall, neighboringBuilding, North Hall (demolished)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: North Hall (demolished)
Context triple: [South Hall, neighboringBuilding, North Hall (demolished)]
  • A. North Hall
    North Hall is a section of the Mausoleum of Mao Zedong in Beijing, China, forming part of the memorial complex dedicated to the founding leader of the People's Republic of China.
  • B. Canton Hall
    Canton Hall is a historic live music and event venue located in Dallas’s Deep Ellum entertainment district.
  • C. Bingham Hall
    Bingham Hall is a historic Yale University dormitory located on the Old Campus in New Haven, Connecticut.
  • D. South Hall
    South Hall is one of the main academic buildings on the University of California, Berkeley campus, housing classrooms, offices, and university departments.
  • E. South Hall
    South Hall is a section of the Mausoleum of Mao Zedong in Beijing, forming part of the memorial complex dedicated to China's former leader.
  • 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: North Hall (demolished)
Triple: [South Hall, neighboringBuilding, North Hall (demolished)]
Generated description
North Hall (demolished) was a former campus building that once stood adjacent to South Hall before being torn down.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: North Hall (demolished)
Target entity description: North Hall (demolished) was a former campus building that once stood adjacent to South Hall before being torn down.
  • A. North Hall
    North Hall is a section of the Mausoleum of Mao Zedong in Beijing, China, forming part of the memorial complex dedicated to the founding leader of the People's Republic of China.
  • B. Canton Hall
    Canton Hall is a historic live music and event venue located in Dallas’s Deep Ellum entertainment district.
  • C. Bingham Hall
    Bingham Hall is a historic Yale University dormitory located on the Old Campus in New Haven, Connecticut.
  • D. South Hall
    South Hall is one of the main academic buildings on the University of California, Berkeley campus, housing classrooms, offices, and university departments.
  • E. South Hall
    South Hall is a section of the Mausoleum of Mao Zedong in Beijing, forming part of the memorial complex dedicated to China's former leader.
  • 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_69a4937bcaac8190a322524ac6f45a5a completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4ab656418819091ecb09e7ede2825 completed March 1, 2026, 9:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69a76d8f639081909690d1ef4c98680e completed March 3, 2026, 11:23 p.m.
NEDg Description generation batch_69a781f5536c81908175d58b6b75adba completed March 4, 2026, 12:51 a.m.
NED2 Entity disambiguation (via description) batch_69a7860e656c8190a08a9999662ba1f1 completed March 4, 2026, 1:08 a.m.
Created at: March 1, 2026, 7:38 p.m.