Triple
T20658322
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Northern Hama Governorate |
E507685
|
entity |
| Predicate | languageMostCommon |
P11430
|
FINISHED |
| Object | Arabic |
—
|
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: Arabic | Statement: [Northern Hama Governorate, languageMostCommon, Arabic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageMostCommon Context triple: [Northern Hama Governorate, languageMostCommon, Arabic]
-
A.
majorityLanguageOf
chosen
Indicates that a given language is the primary or most widely spoken language within a specified group, region, or entity.
-
B.
languageFamilyDominant
Indicates that one language family holds a primary or prevailing status over others within a given context (such as a region, population, or system).
-
C.
languageUsedAs
Indicates that one language is employed in a specific role, function, or context relative to another entity or situation.
-
D.
shareMajorLanguage
Indicates that the entities have at least one primary or major language in common.
-
E.
nationalLanguageSpoken
Indicates that a particular language is officially recognized and commonly used as a national language within a given country or region.
- 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_69e0b4bf58c081908e52a4500e03ff83 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6b2eefd5c8190a71d4be690a6ae0e |
completed | April 20, 2026, 11:12 p.m. |
| PD | Predicate disambiguation | batch_69e5c0315f5081908098707c6455e56e |
completed | April 20, 2026, 5:57 a.m. |
Created at: April 16, 2026, 11:43 a.m.