Triple
T23850207
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | شیراز |
E592140
|
entity |
| Predicate | زبان_رسمی |
P112296
|
FINISHED |
| Object | فارسی |
—
|
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: فارسی | Statement: [شیراز, زبان_رسمی, فارسی]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: زبان_رسمی Context triple: [شیراز, زبان_رسمی, فارسی]
-
A.
officialLanguage
Indicates that a particular language has been formally designated by an authority as the official language used for government, legal, or administrative purposes in a given jurisdiction.
-
B.
hasLanguageOfficial
chosen
Indicates that a language holds official status within a given entity, such as a country, region, or organization.
-
C.
languageOfOfficialAnnouncements
Indicates the language used for formal or official public announcements issued by an authority.
-
D.
shareOfficialLanguage
Indicates that two entities have at least one official language in common.
-
E.
majorityLanguageOf
Indicates that a given language is the primary or most widely spoken language within a specified group, region, or 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_69e25d221d908190b9b502ad31e66a3f |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1c986f7e08190a6d361423946ff05 |
completed | April 29, 2026, 9:04 a.m. |
| PD | Predicate disambiguation | batch_69f1614612b481908c45d99e588882f9 |
completed | April 29, 2026, 1:39 a.m. |
Created at: April 17, 2026, 8:11 p.m.