Triple
T11705132
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ESRB E10+ |
E278218
|
entity |
| Predicate | languageAllowance |
P101345
|
FINISHED |
| Object | infrequent use of mild language |
—
|
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: infrequent use of mild language | Statement: [ESRB E10+, languageAllowance, infrequent use of mild language]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageAllowance Context triple: [ESRB E10+, languageAllowance, infrequent use of mild language]
-
A.
languagePolicyType
Indicates the specific category or type of language policy that governs how languages are used, managed, or regulated in a given context.
-
B.
languagePolicyAspect
Indicates an aspect or component of a broader language policy, such as its goals, rules, or implementation measures.
-
C.
allowsText
Indicates that one entity permits or supports the use, input, or display of textual content in relation to another entity.
-
D.
languageProvision
Indicates that one entity supplies, supports, or makes available a particular language (or set of languages) for use by another entity.
-
E.
languageCriterion
Indicates that a relationship or selection is based on whether something meets a specified language-related requirement or condition.
- 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_69d6aaff2ce88190b4a1e4b341ad5377 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a49c8c38819083d83f5fdec52b7f |
completed | April 10, 2026, 7:19 a.m. |
| PD | Predicate disambiguation | batch_69d88a7b30948190b616a9db5c5488d5 |
completed | April 10, 2026, 5:28 a.m. |
| PDg | Predicate description generation | batch_69d89546a8688190b51455b5e12caf91 |
completed | April 10, 2026, 6:14 a.m. |
Created at: April 8, 2026, 9:40 p.m.