Triple
T27976020
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | سرخپوشان |
E706491
|
entity |
| Predicate | کاربرد در گفتار روزمره |
P29199
|
FINISHED |
| Object | توصیف تیمهای محبوب با پیراهن قرمز |
—
|
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: توصیف تیمهای محبوب با پیراهن قرمز | Statement: [سرخپوشان, کاربرد در گفتار روزمره, توصیف تیمهای محبوب با پیراهن قرمز]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: کاربرد در گفتار روزمره Context triple: [سرخپوشان, کاربرد در گفتار روزمره, توصیف تیمهای محبوب با پیراهن قرمز]
-
A.
typicalLanguageUse
Indicates that one entity is the language most commonly or habitually used by another entity in ordinary communication or contexts.
-
B.
linguisticUsage
chosen
Indicates how a linguistic form, expression, or construction is used in language, such as its typical context, function, or register.
-
C.
usedInSpokenForm
Indicates that something (such as a word, name, or expression) is employed in spoken language or oral communication.
-
D.
general
Indicates that one entity has a broad, non-specific, or overarching relationship or association with another entity.
-
E.
usageAmong
Indicates how frequently or in what manner something is used within a particular group, context, or population.
- 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_69ef96b7f330819090f315318ba6977e |
completed | April 27, 2026, 5:02 p.m. |
| NER | Named-entity recognition | batch_69f65876c52c8190bc889c7a67bd07f3 |
completed | May 2, 2026, 8:03 p.m. |
| PD | Predicate disambiguation | batch_69f6575d89788190aca478e4aea05a65 |
completed | May 2, 2026, 7:58 p.m. |
Created at: April 27, 2026, 7:41 p.m.