Triple

T32331375
Position Surface form Disambiguated ID Type / Status
Subject Adamson University E826060 entity
Predicate hasCollege P113 FINISHED
Object College of Law
The College of Law at Adamson University is the institution’s professional school that offers legal education and training for aspiring lawyers in the Philippines.
 E2003193 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: College of Law | Statement: [Adamson University, hasCollege, College of Law]
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: College of Law
Triple: [Adamson University, hasCollege, College of Law]
Generated description
The College of Law at Adamson University is the institution’s professional school that offers legal education and training for aspiring lawyers in the Philippines.

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_69f34913d9048190befaa634025232be completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6bdefcae881909a82562a56549042 completed May 3, 2026, 3:15 a.m.
NED1 Entity disambiguation (via context triple) batch_6a33e89b9a4c8190a65e3ac7e74296f7 completed June 18, 2026, 12:46 p.m.
NEDg Description generation batch_6a33ea69a55881909e405daf73453474 completed June 18, 2026, 12:54 p.m.
NED2 Entity disambiguation (via description) batch_6a341b155f408190a357f77ca1e78f64 completed June 18, 2026, 4:21 p.m.
Created at: May 1, 2026, 12:47 a.m.