Triple
T596852
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | If Not Now, When? |
E11402
|
entity |
| Predicate | languageStyle |
P6281
|
FINISHED |
| Object | realist |
—
|
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: realist | Statement: [If Not Now, When?, languageStyle, realist]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageStyle Context triple: [If Not Now, When?, languageStyle, realist]
-
A.
languageStandard
Indicates that one entity conforms to, is defined by, or is governed by the language rules, specifications, or conventions established by another entity as a standard.
-
B.
literaryLanguage
Indicates that an entity is expressed, written, or communicated using a particular literary or standardized written language.
-
C.
languageForm
chosen
Indicates the specific linguistic form or expression in which something is conveyed or represented.
-
D.
linguisticType
Indicates the type or category of language or linguistic system associated with an entity (e.g., spoken, signed, written, or other linguistic modality).
-
E.
languageProvision
Indicates that one entity supplies, supports, or makes available a particular language (or set of languages) for use by another entity.
- 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_69a4932779b881908688590d59c71900 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49dc4f7d08190990f70b9b3af6ce5 |
completed | March 1, 2026, 8:12 p.m. |
| PD | Predicate disambiguation | batch_69a49cf59cd0819084e67981cb371e25 |
completed | March 1, 2026, 8:09 p.m. |
Created at: March 1, 2026, 7:35 p.m.