Triple

T27055946
Position Surface form Disambiguated ID Type / Status
Subject Patterns of Enterprise Application Architecture E684896 entity
Predicate describes P264 FINISHED
Object Table Module pattern
The Table Module pattern is an enterprise application architecture style in which a single class handles business logic for all rows in a database table, rather than having one object per row.
 E1754516 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: Table Module pattern | Statement: [Patterns of Enterprise Application Architecture, describes, Table Module pattern]
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: Table Module pattern
Triple: [Patterns of Enterprise Application Architecture, describes, Table Module pattern]
Generated description
The Table Module pattern is an enterprise application architecture style in which a single class handles business logic for all rows in a database table, rather than having one object per row.

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_69ef14829fac8190914bef9ecc3005d7 completed April 27, 2026, 7:47 a.m.
NER Named-entity recognition batch_69f622b35a448190ba08d5c88c883bda completed May 2, 2026, 4:13 p.m.
NED1 Entity disambiguation (via context triple) batch_6a123acb9db0819097fe9e93bc95877d completed May 23, 2026, 11:39 p.m.
NEDg Description generation batch_6a123b8c553081909d6afd9e8a9878af completed May 23, 2026, 11:43 p.m.
NED2 Entity disambiguation (via description) batch_6a123c3427dc8190b6e78dcaabf69fab completed May 23, 2026, 11:45 p.m.
Created at: April 27, 2026, 8:17 a.m.