Triple

T26839165
Position Surface form Disambiguated ID Type / Status
Subject Sun Ke E675720 entity
Predicate positionHeld P8 FINISHED
Object Mayor of Guangzhou
The Mayor of Guangzhou is the chief executive of the Guangzhou municipal government, responsible for overseeing the city's administration, economic development, and public services under the leadership of the local Communist Party committee.
E1745884 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: Mayor of Guangzhou | Statement: [Sun Ke, positionHeld, Mayor of Guangzhou]
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: Mayor of Guangzhou
Triple: [Sun Ke, positionHeld, Mayor of Guangzhou]
Generated description
The Mayor of Guangzhou is the chief executive of the Guangzhou municipal government, responsible for overseeing the city's administration, economic development, and public services under the leadership of the local Communist Party committee.

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_69eee9b8d5e88190a07d3455c0fbb21f completed April 27, 2026, 4:44 a.m.
NER Named-entity recognition batch_69f61b4475588190a4708261118fad78 completed May 2, 2026, 3:41 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12134687b481909fb14dfae3df41f2 completed May 23, 2026, 8:51 p.m.
NEDg Description generation batch_6a121416401481908c0fa6e1c2e9e317 completed May 23, 2026, 8:54 p.m.
NED2 Entity disambiguation (via description) batch_6a1217e349a08190a986e6ce56f5b82d completed May 23, 2026, 9:10 p.m.
Created at: April 27, 2026, 5:06 a.m.