Triple

T27207099
Position Surface form Disambiguated ID Type / Status
Subject Beijing University of Civil Engineering and Architecture E683893 entity
Predicate affiliation P10 FINISHED
Object municipal university system of Beijing
The municipal university system of Beijing is the network of higher education institutions administered by the Beijing municipal government, encompassing various universities and colleges that serve the city’s educational and developmental needs.
E1760087 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: municipal university system of Beijing | Statement: [Beijing University of Civil Engineering and Architecture, affiliation, municipal university system of Beijing]
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: municipal university system of Beijing
Triple: [Beijing University of Civil Engineering and Architecture, affiliation, municipal university system of Beijing]
Generated description
The municipal university system of Beijing is the network of higher education institutions administered by the Beijing municipal government, encompassing various universities and colleges that serve the city’s educational and developmental needs.

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_69eefad339a08190aeacb2a198f1a39b completed April 27, 2026, 5:57 a.m.
NER Named-entity recognition batch_69f625e6138c819093137c0d085b499b completed May 2, 2026, 4:27 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1253a1a57c8190b04539b6762be613 completed May 24, 2026, 1:25 a.m.
NEDg Description generation batch_6a12553613d48190a33bcab491073bbb completed May 24, 2026, 1:32 a.m.
NED2 Entity disambiguation (via description) batch_6a1255e6bc2c8190bfae189c1010f55f completed May 24, 2026, 1:35 a.m.
Created at: April 27, 2026, 9:38 a.m.