Triple
T338579
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dropbear SSH |
E6782
|
entity |
| Predicate | isLicensedUnder |
P8460
|
FINISHED |
| Object | MIT-style license |
—
|
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: MIT-style license | Statement: [Dropbear SSH, isLicensedUnder, MIT-style license]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isLicensedUnder Context triple: [Dropbear SSH, isLicensedUnder, MIT-style license]
-
A.
licenseBuiltAs
Indicates that one entity is constructed, configured, or deployed under the terms or identity of another entity’s license.
-
B.
licenseFamily
Indicates that one license belongs to, is derived from, or is categorized under a broader family or class of related licenses.
-
C.
licenseModel
chosen
Indicates the licensing scheme or framework that governs how something may be used, distributed, or accessed.
-
D.
license
Indicates that one entity has granted another entity formal permission or authorization to use, perform, or exploit something under specified terms.
-
E.
hasLegalInstrument
Indicates that there exists a formal legal document or instrument that establishes, governs, or records the relationship between the related entities.
- 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_69a2e79434908190a9d5afe415153ad9 |
completed | Feb. 28, 2026, 1:03 p.m. |
| NER | Named-entity recognition | batch_69a2eae3a27c81909fc7deb600125fb1 |
completed | Feb. 28, 2026, 1:17 p.m. |
| PD | Predicate disambiguation | batch_69a2e95067e88190a914a1c1d0283dfc |
completed | Feb. 28, 2026, 1:10 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.