Triple

T35545574
Position Surface form Disambiguated ID Type / Status
Subject Bang Rak District E1027202 entity
Predicate contains P35 FINISHED
Object Bangkok Christian College
Bangkok Christian College is one of Thailand’s oldest and most prestigious private boys’ schools, known for its strong academic programs and Christian-based education in central Bangkok.
E2147938 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: Bangkok Christian College | Statement: [Bang Rak District, contains, Bangkok Christian College]
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: Bangkok Christian College
Triple: [Bang Rak District, contains, Bangkok Christian College]
Generated description
Bangkok Christian College is one of Thailand’s oldest and most prestigious private boys’ schools, known for its strong academic programs and Christian-based education in central Bangkok.

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_69f76e008ba08190927acd8e5e0344c8 completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f798098c488190ac1c85d8b5c7a90a completed May 3, 2026, 6:46 p.m.
NED1 Entity disambiguation (via context triple) batch_6a385bc9f13481909d3c2ccf5eb28be2 completed June 21, 2026, 9:46 p.m.
NEDg Description generation batch_6a385f9f80e08190a614ab23db58bcbe completed June 21, 2026, 10:03 p.m.
NED2 Entity disambiguation (via description) batch_6a38606c44408190b74fd416ec90e74c completed June 21, 2026, 10:06 p.m.
Created at: May 3, 2026, 4:04 p.m.