Triple

T7155634
Position Surface form Disambiguated ID Type / Status
Subject Baker House (W7) E166803 entity
Predicate hasDiningFacility P12416 FINISHED
Object Baker Dining
Baker Dining is the dining hall that serves residents and visitors of Baker House at MIT.
E645685 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: Baker Dining | Statement: [Baker House (W7), hasDiningFacility, Baker Dining]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Baker Dining
Context triple: [Baker House (W7), hasDiningFacility, Baker Dining]
  • A. Dockside Diner
    Dockside Diner is a casual, retro-themed quick-service restaurant located on the shores of Echo Lake in Disney’s Hollywood Studios.
  • B. Busch Dining Hall
    Busch Dining Hall is a major campus dining facility at Rutgers University's Busch Campus, serving students, faculty, and staff with a variety of meal options.
  • C. Baker’s
    Baker’s is a regional American supermarket chain known for offering a full range of groceries and household goods.
  • D. Commons Dining Hall
    Commons Dining Hall is a historic central dining facility at Yale University, known for its grand architecture and role as a major campus gathering space.
  • E. Sylvia’s Restaurant
    Sylvia’s Restaurant is a famed soul food eatery in Harlem, New York City, celebrated as a cultural institution and gathering place for locals, celebrities, and politicians alike.
  • 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: Baker Dining
Triple: [Baker House (W7), hasDiningFacility, Baker Dining]
Generated description
Baker Dining is the dining hall that serves residents and visitors of Baker House at MIT.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Baker Dining
Target entity description: Baker Dining is the dining hall that serves residents and visitors of Baker House at MIT.
  • A. Dockside Diner
    Dockside Diner is a casual, retro-themed quick-service restaurant located on the shores of Echo Lake in Disney’s Hollywood Studios.
  • B. Busch Dining Hall
    Busch Dining Hall is a major campus dining facility at Rutgers University's Busch Campus, serving students, faculty, and staff with a variety of meal options.
  • C. Baker’s
    Baker’s is a regional American supermarket chain known for offering a full range of groceries and household goods.
  • D. Commons Dining Hall
    Commons Dining Hall is a historic central dining facility at Yale University, known for its grand architecture and role as a major campus gathering space.
  • E. Sylvia’s Restaurant
    Sylvia’s Restaurant is a famed soul food eatery in Harlem, New York City, celebrated as a cultural institution and gathering place for locals, celebrities, and politicians alike.
  • 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_69c68887a5cc8190bec0ea96227164f7 completed March 27, 2026, 1:39 p.m.
NER Named-entity recognition batch_69c6e80c747c8190a017a2b1c3e78a3f completed March 27, 2026, 8:26 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7adb530388190b68fa05418d3e184 completed March 28, 2026, 10:30 a.m.
NEDg Description generation batch_69c7ae830c74819091d6d65ac6fba32b completed March 28, 2026, 10:33 a.m.
NED2 Entity disambiguation (via description) batch_69c7af1133b08190a32dccf82015c19e completed March 28, 2026, 10:36 a.m.
Created at: March 27, 2026, 2:47 p.m.