Triple

T28292397
Position Surface form Disambiguated ID Type / Status
Subject Old College, University of Edinburgh E713462 entity
Predicate hasPart P35 FINISHED
Object Old College Quad
Old College Quad is the central historic courtyard of the University of Edinburgh’s Old College, known for its neoclassical architecture and role as a focal point of the campus.
 E1810918 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: Old College Quad | Statement: [Old College, University of Edinburgh, hasPart, Old College Quad]
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: Old College Quad
Triple: [Old College, University of Edinburgh, hasPart, Old College Quad]
Generated description
Old College Quad is the central historic courtyard of the University of Edinburgh’s Old College, known for its neoclassical architecture and role as a focal point of the campus.

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_69efb52371d88190a1381c4e58a3b731 completed April 27, 2026, 7:12 p.m.
NER Named-entity recognition batch_69f64484910c81908f66d35cfdaa3cc4 completed May 2, 2026, 6:37 p.m.
NED1 Entity disambiguation (via context triple) batch_6a16072f8f8481909e0bf7c92400a829 completed May 26, 2026, 8:48 p.m.
NEDg Description generation batch_6a160f3cbf8c8190b8e8bccc779c22fc completed May 26, 2026, 9:23 p.m.
NED2 Entity disambiguation (via description) batch_6a160f9fe46c81909cea6bf3850af7c9 completed May 26, 2026, 9:24 p.m.
Created at: April 27, 2026, 11:30 p.m.