Triple
T36480548
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Victory Project |
E898802
|
entity |
| Predicate | technologyTypeInStory |
P1482
|
FINISHED |
| Object | immersive simulation system |
—
|
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: immersive simulation system | Statement: [Victory Project, technologyTypeInStory, immersive simulation system]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: technologyTypeInStory Context triple: [Victory Project, technologyTypeInStory, immersive simulation system]
-
A.
usesTechnologyInStory
Indicates that an entity incorporates or employs a particular technology within the context of a narrative or story.
-
B.
technologyType
chosen
Indicates the specific kind or category of technology associated with an entity or relationship.
-
C.
technologyPioneered
Indicates that an entity was the first or among the first to develop, introduce, or significantly advance a particular technology.
-
D.
technologyDiscussed
Indicates that a conversation, text, or interaction includes discussion or mention of a particular technology.
-
E.
technologyEffect
Indicates the impact or influence that a particular technology has on another entity, system, or outcome.
- 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_69f76e5a0e088190a2b6706aeb41723c |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7c777e924819081a6634f549fe552 |
completed | May 3, 2026, 10:08 p.m. |
| PD | Predicate disambiguation | batch_69f7c477a4d481908f52e55b6688f60c |
completed | May 3, 2026, 9:56 p.m. |
Created at: May 3, 2026, 4:10 p.m.