Triple

T38194062
Position Surface form Disambiguated ID Type / Status
Subject Beihai Municipal Transportation Bureau E1005557 entity
Predicate partOf P40 FINISHED
Object Beihai municipal government system
The Beihai municipal government system is the network of administrative organs and departments responsible for governing and managing public affairs in Beihai City, China.
E306310 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: Beihai municipal government system | Statement: [Beihai Municipal Transportation Bureau, partOf, Beihai municipal government system]
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: Beihai municipal government system
Triple: [Beihai Municipal Transportation Bureau, partOf, Beihai municipal government system]
Generated description
The Beihai municipal government system is the network of administrative organs and departments responsible for governing and managing public affairs in Beihai City, China.

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_69f76dbd22f48190940318cea061e8bb completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69fcb1199dd48190a9e7a3a0db0fd479 completed May 7, 2026, 3:34 p.m.
NED1 Entity disambiguation (via context triple) batch_6a41e00ec4c4819094c092a837133255 completed June 29, 2026, 3:01 a.m.
NEDg Description generation batch_6a41e12f868c8190917fde5775e28d19 completed June 29, 2026, 3:06 a.m.
NED2 Entity disambiguation (via description) batch_6a41e1c14b4c81908b2d6358dbd3ae0f completed June 29, 2026, 3:08 a.m.
Created at: May 3, 2026, 4:29 p.m.