Triple
T8472550
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Workbench |
E200312
|
entity |
| Predicate | fileManagerFor |
P10599
|
FINISHED |
| Object | Amiga filesystem |
—
|
LITERAL 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: Amiga filesystem | Statement: [Workbench, fileManagerFor, Amiga filesystem]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fileManagerFor Context triple: [Workbench, fileManagerFor, Amiga filesystem]
-
A.
fileManager
chosen
Indicates a relationship where an entity manages, organizes, or controls access to files or file-related operations for another entity.
-
B.
fileManagementModel
Indicates a relationship where a model or system is responsible for organizing, storing, modifying, or otherwise managing files and their associated operations.
-
C.
fileSystemSupport
Indicates that one entity (such as a system, application, or device) is capable of recognizing, accessing, and correctly operating with a particular file system or set of file systems.
-
D.
fileUnder
Indicates that one item is categorized, classified, or stored within a particular folder, category, or organizational grouping.
-
E.
fileSystemModel
Indicates a relationship where an entity serves as or is associated with a particular file system model or representation.
- F. None of above.
Provenance (3 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_69ca831a4f348190bfdd09250e86ae35 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe4f4fbf481909e4fd7c078b27477 |
completed | March 31, 2026, 3:15 p.m. |
| PD | Predicate disambiguation | batch_69cbd104250c8190b4c499dcc9937494 |
completed | March 31, 2026, 1:49 p.m. |
Created at: March 30, 2026, 6:11 p.m.