Triple

T35108751
Position Surface form Disambiguated ID Type / Status
Subject Shanghai military government E1013225 entity
Predicate executiveBody P1001 FINISHED
Object military governor’s office of Shanghai
The military governor’s office of Shanghai was the central administrative authority responsible for overseeing military and civil affairs in Shanghai under a military government.
E1013225 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: military governor’s office of Shanghai | Statement: [Shanghai military government, executiveBody, military governor’s office of Shanghai]
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: military governor’s office of Shanghai
Triple: [Shanghai military government, executiveBody, military governor’s office of Shanghai]
Generated description
The military governor’s office of Shanghai was the central administrative authority responsible for overseeing military and civil affairs in Shanghai under a military government.

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_69f76dd659d08190bcdc00d37caafb62 completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69f78c14e4788190923e0d644e8800ca completed May 3, 2026, 5:55 p.m.
NED1 Entity disambiguation (via context triple) batch_6a37cffac58481909a973bf9513a4011 completed June 21, 2026, 11:50 a.m.
NEDg Description generation batch_6a37d0a8cc748190989640faa3a1c600 completed June 21, 2026, 11:53 a.m.
NED2 Entity disambiguation (via description) batch_6a37d140ec9481909f08dbd8c40d1ec7 completed June 21, 2026, 11:55 a.m.
Created at: May 3, 2026, 4:01 p.m.