Triple

T27325729
Position Surface form Disambiguated ID Type / Status
Subject Iwate University E689637 entity
Predicate hasFaculty P141 FINISHED
Object Faculty of Education
The Faculty of Education at Iwate University is an academic division dedicated to training future teachers and conducting research in educational theory and practice.
 E1765965 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: [Iwate 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: [Iwate University, hasFaculty, Faculty of Education]
Generated description
The Faculty of Education at Iwate University is an academic division dedicated to training future teachers 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_69ef355d4cb08190ab032c0a2e7d3753 completed April 27, 2026, 10:07 a.m.
NER Named-entity recognition batch_69f627edd6d08190a059d44edecfb368 completed May 2, 2026, 4:35 p.m.
NED1 Entity disambiguation (via context triple) batch_6a129cb8941481909bd229aa81a72fce completed May 24, 2026, 6:37 a.m.
NEDg Description generation batch_6a129d7477bc8190ac1956dc68c4df75 completed May 24, 2026, 6:40 a.m.
NED2 Entity disambiguation (via description) batch_6a129e4151208190995590e78cf35502 completed May 24, 2026, 6:44 a.m.
Created at: April 27, 2026, 11:35 a.m.