Triple

T37131306
Position Surface form Disambiguated ID Type / Status
Subject PEP 657 E919523 entity
Predicate hasTitle P38 FINISHED
Object Include Fine-Grained Error Locations in Tracebacks
"Include Fine-Grained Error Locations in Tracebacks" is a Python Enhancement Proposal (PEP 657) that introduces more precise error location information in Python tracebacks to improve debugging and error diagnosis.
 E2214099 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: Include Fine-Grained Error Locations in Tracebacks | Statement: [PEP 657, hasTitle, Include Fine-Grained Error Locations in Tracebacks]
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: Include Fine-Grained Error Locations in Tracebacks
Triple: [PEP 657, hasTitle, Include Fine-Grained Error Locations in Tracebacks]
Generated description
"Include Fine-Grained Error Locations in Tracebacks" is a Python Enhancement Proposal (PEP 657) that introduces more precise error location information in Python tracebacks to improve debugging and error diagnosis.

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_69f76e9d13e48190a108f7fbf80ff375 completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69fb303ddb548190a7931d7a42dca88a completed May 6, 2026, 12:12 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3f6a23b06c81909e1067166f0c9c0f completed June 27, 2026, 6:13 a.m.
NEDg Description generation batch_6a3f6b95bae48190a8d7210e29994c81 completed June 27, 2026, 6:20 a.m.
NED2 Entity disambiguation (via description) batch_6a3f6c102114819088b32c3f81f9284c completed June 27, 2026, 6:22 a.m.
Created at: May 3, 2026, 4:15 p.m.