Triple

T26307006
Position Surface form Disambiguated ID Type / Status
Subject Xuanwu District E661710 entity
Predicate governingBody P46 FINISHED
Object Xuanwu District People’s Government
Xuanwu District People’s Government is the local administrative authority responsible for governing and managing public affairs in Xuanwu District.
E1718345 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: Xuanwu District People’s Government | Statement: [Xuanwu District, governingBody, Xuanwu District People’s 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: Xuanwu District People’s Government
Triple: [Xuanwu District, governingBody, Xuanwu District People’s Government]
Generated description
Xuanwu District People’s Government is the local administrative authority responsible for governing and managing public affairs in Xuanwu District.

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_69ee812dacfc81908484aade9120fba9 completed April 26, 2026, 9:18 p.m.
NER Named-entity recognition batch_69f60ee3b22081909815d1ec423b02ae completed May 2, 2026, 2:49 p.m.
NED1 Entity disambiguation (via context triple) batch_6a118fd048b48190b2cdc48f0c766067 completed May 23, 2026, 11:30 a.m.
NEDg Description generation batch_6a11908b60208190947e35ec81b2db01 completed May 23, 2026, 11:33 a.m.
NED2 Entity disambiguation (via description) batch_6a11918f1dd48190be4ff6b151a01943 completed May 23, 2026, 11:37 a.m.
Created at: April 26, 2026, 10:19 p.m.