Triple
T29910893
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alembic |
E759673
|
entity |
| Predicate | usedInSoftware |
P105842
|
FINISHED |
| Object | Autodesk Maya |
—
|
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: Autodesk Maya | Statement: [Alembic, usedInSoftware, Autodesk Maya]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedInSoftware Context triple: [Alembic, usedInSoftware, Autodesk Maya]
-
A.
areUsedIn
Indicates that certain entities serve as components, tools, or resources within a particular process, context, or application.
-
B.
usesSoftware
Indicates that one entity employs or operates a particular software application or system to perform tasks or functions.
-
C.
usedInComputingSystems
chosen
Indicates that something is employed or applied within computing systems, such as hardware, software, or digital infrastructures, to perform functions or operations.
-
D.
usedInPractice
Indicates that something is actually applied or implemented in real-world practice rather than just being theoretical or proposed.
-
E.
alsoUsedIn
Indicates that something is additionally employed, applied, or present in another context, setting, or use case beyond the primary one.
- 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_69f224600590819085e148a01c056ef6 |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69fd32848ea88190a71e6df402bbb30e |
completed | May 8, 2026, 12:47 a.m. |
| PD | Predicate disambiguation | batch_69fd2d7e95588190991d5f21e25155df |
completed | May 8, 2026, 12:25 a.m. |
Created at: April 29, 2026, 6:10 p.m.