Triple

T29276262
Position Surface form Disambiguated ID Type / Status
Subject Department of Education, Culture and Sports E742249 entity
Predicate historicalPredecessorOf P3444 FINISHED
Object Department of Education
The Department of Education is the Philippine government agency responsible for overseeing and regulating the country’s basic education system.
E1859795 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: Department of Education | Statement: [Department of Education, Culture and Sports, historicalPredecessorOf, Department 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: Department of Education
Triple: [Department of Education, Culture and Sports, historicalPredecessorOf, Department of Education]
Generated description
The Department of Education is the Philippine government agency responsible for overseeing and regulating the country’s basic education system.

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_69f0912124d48190a046642b69407f4c completed April 28, 2026, 10:51 a.m.
NER Named-entity recognition batch_69f665122c9c8190bc72315f4ad39fa1 completed May 2, 2026, 8:56 p.m.
NED1 Entity disambiguation (via context triple) batch_6a25c0dfaa8c8190abd6e4e49b11dc3b completed June 7, 2026, 7:05 p.m.
NEDg Description generation batch_6a25c64203048190a2268e2aaa439e8d completed June 7, 2026, 7:28 p.m.
NED2 Entity disambiguation (via description) batch_6a25c695fec48190949045da6d3828c2 completed June 7, 2026, 7:29 p.m.
Created at: April 28, 2026, 12:51 p.m.