Triple

T34483018
Position Surface form Disambiguated ID Type / Status
Subject Sogang University E885239 entity
Predicate hasFaculty P141 FINISHED
Object School of Media, Arts, and Science
The School of Media, Arts, and Science is an academic division of Sogang University specializing in interdisciplinary education and research across media studies, creative arts, and related technologies.
E2098979 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: School of Media, Arts, and Science | Statement: [Sogang University, hasFaculty, School of Media, Arts, and Science]
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: School of Media, Arts, and Science
Triple: [Sogang University, hasFaculty, School of Media, Arts, and Science]
Generated description
The School of Media, Arts, and Science is an academic division of Sogang University specializing in interdisciplinary education and research across media studies, creative arts, and related technologies.

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_69f349c947fc81909d30b53c194d6ea1 completed April 30, 2026, 12:23 p.m.
NER Named-entity recognition batch_69f71ccfef3481908c5df0a04f9cb980 completed May 3, 2026, 10 a.m.
NED1 Entity disambiguation (via context triple) batch_6a37213a07f08190954ce3fa792f7d7a completed June 20, 2026, 11:24 p.m.
NEDg Description generation batch_6a3721ea92a48190bb0fc6df5267138e completed June 20, 2026, 11:27 p.m.
NED2 Entity disambiguation (via description) batch_6a3722d05034819087a1399552af21cc completed June 20, 2026, 11:31 p.m.
Created at: May 1, 2026, 2:01 a.m.