Triple
T18799663
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NetworkX |
E459727
|
entity |
| Predicate | importName |
P56253
|
FINISHED |
| Object | networkx |
—
|
NE NERFINISHED |
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: networkx | Statement: [NetworkX, importName, networkx]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: networkx Context triple: [NetworkX, importName, networkx]
-
A.
NetworkX
chosen
NetworkX is a Python library for creating, analyzing, and visualizing complex networks and graphs.
-
B.
GraphX
GraphX is Apache Spark’s distributed graph processing framework that enables large-scale graph computation and analysis using Spark’s resilient distributed datasets (RDDs).
-
C.
CyberGraphX
CyberGraphX is a graphics subsystem and API originally developed for Amiga systems, providing advanced graphics card support and hardware-accelerated rendering.
-
D.
Chart Information Network
Chart Information Network was the former name of the UK-based organization now known as the Official Charts Company, which compiles and publishes the country's official music charts.
-
E.
DGL
DGL is the vehicle registration code assigned to the town of Głogów in Poland.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8d398c7d4819091cb2f7e48948aeb |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e5a02273b481909bc250144a0ace32 |
completed | April 20, 2026, 3:40 a.m. |
Created at: April 10, 2026, 11:53 a.m.