Triple
T8681900
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FSF-endorsed distributions list |
E206056
|
entity |
| Predicate | isBasedOnPolicy |
P57657
|
FINISHED |
| Object | FSF position on nonfree software |
—
|
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: FSF position on nonfree software | Statement: [FSF-endorsed distributions list, isBasedOnPolicy, FSF position on nonfree software]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isBasedOnPolicy Context triple: [FSF-endorsed distributions list, isBasedOnPolicy, FSF position on nonfree software]
-
A.
isOnPolicy
Indicates that an action, configuration, or behavior complies with and adheres to a specified policy or set of rules.
-
B.
containsPolicyOn
chosen
Indicates that one entity includes, references, or incorporates a specific policy within it.
-
C.
appliesToPolicy
Indicates that something is relevant or applicable to a particular policy.
-
D.
supportsPolicy
Indicates that one entity endorses, backs, or is in favor of a particular policy or set of policies.
-
E.
usesPolicyModel
Indicates that one entity applies, relies on, or operates according to a particular policy model.
- 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_69ca835379688190aa06b9d98e684d58 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc4ae82e508190b0243328e98fcb1d |
completed | March 31, 2026, 10:30 p.m. |
| PD | Predicate disambiguation | batch_69cc4567b5c881908d9ec5dcfc783fac |
completed | March 31, 2026, 10:06 p.m. |
Created at: March 30, 2026, 6:32 p.m.