Triple
T22813649
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | TFile |
E565045
|
entity |
| Predicate | accessibleFrom |
P1985
|
FINISHED |
| Object | PyROOT |
—
|
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: PyROOT | Statement: [TFile, accessibleFrom, PyROOT]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: PyROOT Context triple: [TFile, accessibleFrom, PyROOT]
-
A.
ROOT
chosen
ROOT is a widely used object-oriented data analysis framework and file format developed at CERN for storing, processing, and visualizing large volumes of high-energy physics data.
-
B.
Pyright
Pyright is a fast, static type checker for Python that provides comprehensive type analysis, including support for advanced features like generic types.
-
C.
Pythonidae
Pythonidae is a family of nonvenomous constrictor snakes that includes pythons found across Africa, Asia, and Australia.
-
D.
PyTables
PyTables is a Python library that provides efficient management, querying, and storage of large amounts of data using the HDF5 format.
-
E.
Cython
Cython is a programming language and compiler that extends Python with static typing and direct C/C++ integration to generate fast, optimized extension modules.
- 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_69e2458426188190b58b8ab4844fe420 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17d62b0ec8190ac22909192e8a876 |
completed | April 29, 2026, 3:39 a.m. |
Created at: April 17, 2026, 3:32 p.m.