Triple
T15011593
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sawanih |
E377849
|
entity |
| Predicate | literaryLanguageVariant |
P5595
|
FINISHED |
| Object | Indo-Persian |
—
|
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: Indo-Persian | Statement: [Sawanih, literaryLanguageVariant, Indo-Persian]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: literaryLanguageVariant Context triple: [Sawanih, literaryLanguageVariant, Indo-Persian]
-
A.
linguisticVariant
Indicates that one linguistic form is an alternative version or expression of another within the same or closely related language context.
-
B.
languageVariant
chosen
Indicates that one language is a variant, dialect, or localized form of another language.
-
C.
officialLanguageVariant
Indicates that one language variety is an officially recognized form or version of another language within a specific jurisdiction or context.
-
D.
literaryLanguage
Indicates that an entity is expressed, written, or communicated using a particular literary or standardized written language.
-
E.
labelLanguageVariant
Indicates that one label is a language-specific variant or localized form of another label.
- 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_69d85cd3a3c881908c71fc424d459c17 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded7613cec8190ac25e3f68c5d0edf |
completed | April 15, 2026, 12:10 a.m. |
| PD | Predicate disambiguation | batch_69de9a6531a88190acde65199a477350 |
completed | April 14, 2026, 7:49 p.m. |
Created at: April 10, 2026, 2:55 a.m.