Triple

T6350124
Position Surface form Disambiguated ID Type / Status
Subject Daoguang Emperor E142847 entity
Predicate personalName P24312 FINISHED
Object Minning
Minning was the personal name of the Daoguang Emperor, a Qing dynasty ruler of China in the early to mid-19th century.
 E587317 NE FINISHED

How this triple was built (4 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: Minning | Statement: [Daoguang Emperor, personalName, Minning]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Minning
Context triple: [Daoguang Emperor, personalName, Minning]
  • A. Miners
    Miners is the nickname for the University of Texas at El Paso’s athletic teams, most prominently its NCAA Division I football program.
  • B. Placer
    Placer is the former historic name of the town now known as Loomis in Placer County, California.
  • C. Minns
    Minns is the namesake of the Minns Evening Normal School, an institution historically associated with teacher education.
  • D. Miner
    Miner is a surname of English origin historically associated with the occupation of mining.
  • E. Minin
    Minin is a Russian surname most famously borne by Kuzma Minin, a merchant from Nizhny Novgorod who became a national hero for organizing resistance against Polish invaders in the early 17th century.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
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: Minning
Triple: [Daoguang Emperor, personalName, Minning]
Generated description
Minning was the personal name of the Daoguang Emperor, a Qing dynasty ruler of China in the early to mid-19th century.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Minning
Target entity description: Minning was the personal name of the Daoguang Emperor, a Qing dynasty ruler of China in the early to mid-19th century.
  • A. Miners
    Miners is the nickname for the University of Texas at El Paso’s athletic teams, most prominently its NCAA Division I football program.
  • B. Placer
    Placer is the former historic name of the town now known as Loomis in Placer County, California.
  • C. Minns
    Minns is the namesake of the Minns Evening Normal School, an institution historically associated with teacher education.
  • D. Miner
    Miner is a surname of English origin historically associated with the occupation of mining.
  • E. Minin
    Minin is a Russian surname most famously borne by Kuzma Minin, a merchant from Nizhny Novgorod who became a national hero for organizing resistance against Polish invaders in the early 17th century.
  • F. None of above. chosen

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_69c008d6dcbc8190aa1c2f1fd8916b42 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c067bcec2c8190bb383605847b0f0b completed March 22, 2026, 10:05 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6044fcd288190abdc5746e2904928 completed March 27, 2026, 4:15 a.m.
NEDg Description generation batch_69c6083573c48190ba629b72cbaf4ef3 completed March 27, 2026, 4:31 a.m.
NED2 Entity disambiguation (via description) batch_69c6092e12d481909b41fd35d6ae1d57 completed March 27, 2026, 4:35 a.m.
Created at: March 22, 2026, 4:31 p.m.