Triple
T18050949
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | argparse |
E431924
|
entity |
| Predicate | providesFunction |
P16244
|
FINISHED |
| Object |
ArgumentParser.add_argument
ArgumentParser.add_argument is a core argparse method in Python used to define and configure the command-line arguments that a program accepts.
|
E1303142
|
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: ArgumentParser.add_argument | Statement: [argparse, providesFunction, ArgumentParser.add_argument]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: ArgumentParser.add_argument Context triple: [argparse, providesFunction, ArgumentParser.add_argument]
-
A.
argparse
argparse is a Python module for parsing command-line arguments and options, enabling easy creation of user-friendly CLI interfaces.
-
B.
Master Argument
The Master Argument is a famous logical paradox from ancient Greek philosophy that challenges the compatibility of possibility, necessity, and future contingents.
-
C.
ARG
ARG is the three-letter ISO 3166-1 alpha-3 country code that uniquely identifies Argentina in international standards and data systems.
-
D.
ARG
ARG is the National Rail station code assigned to Arnos Grove station in London.
-
E.
Arg complex
The Arg complex is a fortified governmental and residential compound in central Kabul that serves as the seat of Afghanistan’s presidency and key state institutions.
- 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: ArgumentParser.add_argument Triple: [argparse, providesFunction, ArgumentParser.add_argument]
Generated description
ArgumentParser.add_argument is a core argparse method in Python used to define and configure the command-line arguments that a program accepts.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: ArgumentParser.add_argument Target entity description: ArgumentParser.add_argument is a core argparse method in Python used to define and configure the command-line arguments that a program accepts.
-
A.
argparse
argparse is a Python module for parsing command-line arguments and options, enabling easy creation of user-friendly CLI interfaces.
-
B.
Master Argument
The Master Argument is a famous logical paradox from ancient Greek philosophy that challenges the compatibility of possibility, necessity, and future contingents.
-
C.
ARG
ARG is the three-letter ISO 3166-1 alpha-3 country code that uniquely identifies Argentina in international standards and data systems.
-
D.
ARG
ARG is the National Rail station code assigned to Arnos Grove station in London.
-
E.
Arg complex
The Arg complex is a fortified governmental and residential compound in central Kabul that serves as the seat of Afghanistan’s presidency and key state institutions.
- 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_69e4bff57ea08190a30a87993f7d3299 |
completed | April 19, 2026, 11:43 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.