Triple

T18051267
Position Surface form Disambiguated ID Type / Status
Subject contextlib E431930 entity
Predicate defines P264 FINISHED
Object ExitStack
ExitStack is a Python context manager utility that allows you to dynamically enter and manage multiple context managers and cleanup callbacks in a flexible, programmatic way.
 E1303148 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: ExitStack | Statement: [contextlib, defines, ExitStack]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: ExitStack
Context triple: [contextlib, defines, ExitStack]
  • A. Operation Stack
    Operation Stack was a traffic management system used in Kent, England, to queue freight traffic on the M20 motorway during disruptions to cross-Channel services.
  • B. Stack$
    Stack$ is a musical act connected to American singer and television personality Brooke Hogan.
  • C. Stack
    Stack is a surname most notably associated with American actor and television host Robert Stack.
  • D. Stack
    Stack is a cross-platform build tool and package manager for Haskell that simplifies project setup, dependency management, and reproducible builds.
  • E. Stackless Python
    Stackless Python is an enhanced version of the Python interpreter that provides lightweight microthreads and improved concurrency support without relying on the C call stack.
  • 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: ExitStack
Triple: [contextlib, defines, ExitStack]
Generated description
ExitStack is a Python context manager utility that allows you to dynamically enter and manage multiple context managers and cleanup callbacks in a flexible, programmatic way.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: ExitStack
Target entity description: ExitStack is a Python context manager utility that allows you to dynamically enter and manage multiple context managers and cleanup callbacks in a flexible, programmatic way.
  • A. Operation Stack
    Operation Stack was a traffic management system used in Kent, England, to queue freight traffic on the M20 motorway during disruptions to cross-Channel services.
  • B. Stack$
    Stack$ is a musical act connected to American singer and television personality Brooke Hogan.
  • C. Stack
    Stack is a surname most notably associated with American actor and television host Robert Stack.
  • D. Stack
    Stack is a cross-platform build tool and package manager for Haskell that simplifies project setup, dependency management, and reproducible builds.
  • E. Stackless Python
    Stackless Python is an enhanced version of the Python interpreter that provides lightweight microthreads and improved concurrency support without relying on the C call stack.
  • 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_69d8b906482481908183315b9ecf9994 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4c0fe4f1881908fa8485cb3ccfa44 completed April 19, 2026, 11:48 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0349bf5fc48190afd460025b1fe505 completed May 12, 2026, 3:39 p.m.
NEDg Description generation batch_6a034b7197e48190ae62f25f2fb434b6 completed May 12, 2026, 3:46 p.m.
NED2 Entity disambiguation (via description) batch_6a034c08c12081908fee77fbb97b5840 completed May 12, 2026, 3:49 p.m.
Created at: April 10, 2026, 10:25 a.m.