Triple
T38338048
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hoth system |
E1038014
|
entity |
| Predicate | hasTechnologyUsed |
P133726
|
FINISHED |
| Object | T-47 airspeeder |
—
|
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: T-47 airspeeder | Statement: [Hoth system, hasTechnologyUsed, T-47 airspeeder]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTechnologyUsed Context triple: [Hoth system, hasTechnologyUsed, T-47 airspeeder]
-
A.
hasTechnologyPresence
Indicates that a particular technology exists, is implemented, or is actively in use within a given entity, context, or environment.
-
B.
hasTechnologySystem
chosen
Indicates that one entity possesses, utilizes, or is supported by a particular technology system.
-
C.
hasCommunicationUse
Indicates that something is used for, or serves the purpose of, communication.
-
D.
usesTechnologyInStory
Indicates that an entity incorporates or employs a particular technology within the context of a narrative or story.
-
E.
technologyUsedFor
Indicates that a particular technology is employed or applied to accomplish, support, or enable a specific purpose, task, or function.
- 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_69f76e20d65c81909619ac0dd85c56f0 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69fedec693b08190b0f8bfdb921e0766 |
completed | May 9, 2026, 7:14 a.m. |
| PD | Predicate disambiguation | batch_69fede16c1d48190a20d8a9c5722c307 |
completed | May 9, 2026, 7:11 a.m. |
Created at: May 3, 2026, 4:30 p.m.