Triple
T17518597
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Minmatar Republic |
E426627
|
entity |
| Predicate | technologyStyle |
P127752
|
FINISHED |
| Object | improvised engineering |
—
|
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: improvised engineering | Statement: [Minmatar Republic, technologyStyle, improvised engineering]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: technologyStyle Context triple: [Minmatar Republic, technologyStyle, improvised engineering]
-
A.
technologyType
Indicates the specific kind or category of technology associated with an entity or relationship.
-
B.
technologyName
Indicates the specific name or designation of a technology associated with an entity.
-
C.
technologyClass
Indicates the classification or category of technology to which an entity belongs.
-
D.
technologyIncludes
Indicates that one technology encompasses, contains, or incorporates another technology as part of its components, features, or implementation.
-
E.
technologyTrend
Indicates a relationship where a technology is characterized as part of a broader pattern of change or direction in technological development over time.
- F. None of above. chosen
Provenance (4 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_69d889dd9164819087b1dc3c9240c870 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e452d0daa48190be69aff32b0324bc |
completed | April 19, 2026, 3:58 a.m. |
| PD | Predicate disambiguation | batch_69e3b4f8b9888190aa8a45e09acf4319 |
completed | April 18, 2026, 4:44 p.m. |
| PDg | Predicate description generation | batch_69e3bbb37d148190b7f38599c06594ee |
completed | April 18, 2026, 5:13 p.m. |
Created at: April 10, 2026, 5:49 a.m.