Triple

T27533286
Position Surface form Disambiguated ID Type / Status
Subject Oxford MCCU E695027 entity
Predicate hasRivalryWith P893 FINISHED
Object Cambridge MCCU
Cambridge MCCU is a university cricket centre of excellence representing Cambridge-based institutions in first-class and other competitive matches within the English cricket structure.
E1781748 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: Cambridge MCCU | Statement: [Oxford MCCU, hasRivalryWith, Cambridge MCCU]
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: Cambridge MCCU
Triple: [Oxford MCCU, hasRivalryWith, Cambridge MCCU]
Generated description
Cambridge MCCU is a university cricket centre of excellence representing Cambridge-based institutions in first-class and other competitive matches within the English cricket structure.

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_69ef538608b081908b9f659bb09d5e0f completed April 27, 2026, 12:16 p.m.
NER Named-entity recognition batch_69f62f5866a48190ad6e727cfe56b234 completed May 2, 2026, 5:07 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12d0c6f5ac81909f56e8a9a42c566b completed May 24, 2026, 10:19 a.m.
NEDg Description generation batch_6a12d169e8888190bf3c8e7f0718a3a5 completed May 24, 2026, 10:22 a.m.
NED2 Entity disambiguation (via description) batch_6a12d23dc1b48190aa7f52797b82db62 completed May 24, 2026, 10:26 a.m.
Created at: April 27, 2026, 1:27 p.m.