Triple

T31034680
Position Surface form Disambiguated ID Type / Status
Subject Edge Hill University E790822 entity
Predicate hasFaculty P141 FINISHED
Object Faculty of Education
The Faculty of Education is the academic division of Edge Hill University responsible for training teachers and education professionals and conducting research in educational theory and practice.
 E1941869 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: Faculty of Education | Statement: [Edge Hill University, hasFaculty, Faculty of Education]
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: Faculty of Education
Triple: [Edge Hill University, hasFaculty, Faculty of Education]
Generated description
The Faculty of Education is the academic division of Edge Hill University responsible for training teachers and education professionals and conducting research in educational theory and practice.

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_69f224c97a788190b5da1ead6038a74e completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f694f4f6e881908e00ff63a092f717 completed May 3, 2026, 12:21 a.m.
NED1 Entity disambiguation (via context triple) batch_6a29184f12448190838fc6d0f0e3f8c7 completed June 10, 2026, 7:54 a.m.
NEDg Description generation batch_6a291968577081908da453b3058374f3 completed June 10, 2026, 7:59 a.m.
NED2 Entity disambiguation (via description) batch_6a291a095c848190ae3fc5f3e481756b completed June 10, 2026, 8:02 a.m.
Created at: April 29, 2026, 8:59 p.m.