Triple

T28283862
Position Surface form Disambiguated ID Type / Status
Subject Zuiweng E713226 entity
Predicate meaning P129 FINISHED
Object Drunken Old Man
Drunken Old Man is a poetic epithet most famously associated with the Northern Song literatus Ouyang Xiu, evoking the image of a carefree, wine-loving scholar immersed in nature and verse.
 E1810712 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: Drunken Old Man | Statement: [Zuiweng, meaning, Drunken Old Man]
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: Drunken Old Man
Triple: [Zuiweng, meaning, Drunken Old Man]
Generated description
Drunken Old Man is a poetic epithet most famously associated with the Northern Song literatus Ouyang Xiu, evoking the image of a carefree, wine-loving scholar immersed in nature and verse.

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_69efb52371d88190a1381c4e58a3b731 completed April 27, 2026, 7:12 p.m.
NER Named-entity recognition batch_69f6447df07c8190bbbd284a8386c02e completed May 2, 2026, 6:37 p.m.
NED1 Entity disambiguation (via context triple) batch_6a160728a9108190b774efc094320cdb completed May 26, 2026, 8:48 p.m.
NEDg Description generation batch_6a1613ef6698819089eb6e89c8fff844 completed May 26, 2026, 9:43 p.m.
NED2 Entity disambiguation (via description) batch_6a1614512f9881908fa9fe919e32a1e4 completed May 26, 2026, 9:44 p.m.
Created at: April 27, 2026, 11:24 p.m.