Triple

T37607277
Position Surface form Disambiguated ID Type / Status
Subject Guangfeng District E935687 entity
Predicate hasAdministrativeCenter P1474 FINISHED
Object Guangfeng District government
Guangfeng District government is the primary local administrative authority responsible for governing and managing public affairs in Guangfeng District, China.
E2233583 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: Guangfeng District government | Statement: [Guangfeng District, hasAdministrativeCenter, Guangfeng District government]
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: Guangfeng District government
Triple: [Guangfeng District, hasAdministrativeCenter, Guangfeng District government]
Generated description
Guangfeng District government is the primary local administrative authority responsible for governing and managing public affairs in Guangfeng District, 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_69f76ed0a85481909254a8a89090c826 completed May 3, 2026, 3:50 p.m.
NER Named-entity recognition batch_69fba9026df4819093c25a9373f32691 completed May 6, 2026, 8:48 p.m.
NED1 Entity disambiguation (via context triple) batch_6a40a80a30408190ad19af26da098842 completed June 28, 2026, 4:50 a.m.
NEDg Description generation batch_6a40a86b1f388190876a2a5080f668ea completed June 28, 2026, 4:51 a.m.
NED2 Entity disambiguation (via description) batch_6a40a8c619fc81908b7f0b2b3c614aa2 completed June 28, 2026, 4:53 a.m.
Created at: May 3, 2026, 4:18 p.m.