Triple

T35029624
Position Surface form Disambiguated ID Type / Status
Subject Khlong Luang E1010441 entity
Predicate hasEducationalInstitution P113 FINISHED
Object Valaya Alongkorn Rajabhat University
Valaya Alongkorn Rajabhat University is a Thai public university in the Rajabhat system, focused on teacher education and community-oriented higher education.
E2128334 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: Valaya Alongkorn Rajabhat University | Statement: [Khlong Luang, hasEducationalInstitution, Valaya Alongkorn Rajabhat University]
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: Valaya Alongkorn Rajabhat University
Triple: [Khlong Luang, hasEducationalInstitution, Valaya Alongkorn Rajabhat University]
Generated description
Valaya Alongkorn Rajabhat University is a Thai public university in the Rajabhat system, focused on teacher education and community-oriented higher education.

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_69f76dccf0108190af43b465d3750196 completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69f7854569208190a5c3bd8e5f8a8ea3 completed May 3, 2026, 5:26 p.m.
NED1 Entity disambiguation (via context triple) batch_6a37d93fb450819094781ba06f7e1bb3 completed June 21, 2026, 12:29 p.m.
NEDg Description generation batch_6a37dd7aa0e88190a1b163608970b643 completed June 21, 2026, 12:47 p.m.
NED2 Entity disambiguation (via description) batch_6a37de263a988190bc9f98df87175e41 completed June 21, 2026, 12:50 p.m.
Created at: May 3, 2026, 4:01 p.m.