Triple
T6790534
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Open Software License 3.0 |
E155918
|
entity |
| Predicate | licenseTextLanguage |
P42636
|
FINISHED |
| Object | English |
—
|
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: English | Statement: [Open Software License 3.0, licenseTextLanguage, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: licenseTextLanguage Context triple: [Open Software License 3.0, licenseTextLanguage, English]
-
A.
license
Indicates that one entity has granted another entity formal permission or authorization to use, perform, or exploit something under specified terms.
-
B.
licensePreference
Indicates a party’s chosen or prioritized type of license to use, grant, or operate under in a given context.
-
C.
legalProtectionOfLanguage
Indicates that a language is safeguarded or regulated by formal legal measures, such as laws, policies, or constitutional provisions.
-
D.
licenseFor
Indicates that one entity grants or holds formal permission or authorization for another entity to perform an activity, use a resource, or operate under specified conditions.
-
E.
languageOfDocumentation
chosen
Indicates the language in which the documentation for an entity is written or provided.
- 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_69c6881770fc8190972b2906390380f5 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d2acbfc0819081f2d6cebfb91765 |
completed | March 27, 2026, 6:55 p.m. |
| PD | Predicate disambiguation | batch_69c6d0979ce0819094678896da4e3169 |
completed | March 27, 2026, 6:46 p.m. |
Created at: March 27, 2026, 2:15 p.m.