Triple

T25567931
Position Surface form Disambiguated ID Type / Status
Subject Trinity Hall courts and buildings complex E640888 entity
Predicate hasPart P35 FINISHED
Object Old Library building
The Old Library building is a historic structure within Trinity Hall, Cambridge, traditionally used to house the college’s library collections and academic spaces.
 E1685567 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 Library building | Statement: [Trinity Hall courts and buildings complex, hasPart, Old Library building]
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 Library building
Triple: [Trinity Hall courts and buildings complex, hasPart, Old Library building]
Generated description
The Old Library building is a historic structure within Trinity Hall, Cambridge, traditionally used to house the college’s library collections and academic spaces.

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_69e75dc1beb08190bac7d76b8d6e7bc4 completed April 21, 2026, 11:21 a.m.
NER Named-entity recognition batch_69f5f8fe0abc8190862167a5d282e107 completed May 2, 2026, 1:15 p.m.
NED1 Entity disambiguation (via context triple) batch_6a10b758aa9881908eaa5b3b02b4c019 completed May 22, 2026, 8:06 p.m.
NEDg Description generation batch_6a10b7d88f6c8190a73108b86191ea5d completed May 22, 2026, 8:08 p.m.
NED2 Entity disambiguation (via description) batch_6a10b91b5be08190a85532fe02db813e completed May 22, 2026, 8:14 p.m.
Created at: April 21, 2026, 3:50 p.m.