Triple
T2334299
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Najd |
E44274
|
entity |
| Predicate | language |
P15
|
FINISHED |
| Object | Najdi Arabic |
E36756
|
NE 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: Najdi Arabic | Statement: [Najd, language, Najdi Arabic]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Najdi Arabic Context triple: [Najd, language, Najdi Arabic]
-
A.
Najdi Arabic
chosen
Najdi Arabic is a central Arabian dialect of the Arabic language spoken primarily in the Najd region of Saudi Arabia.
-
B.
Razihi Arabic
Razihi Arabic is a highly distinctive and conservative Arabic variety spoken in the Razih region of northwestern Yemen, noted for preserving archaic linguistic features.
-
C.
Arabic
Arabic is a Semitic language widely spoken across the Arab world and used as a liturgical language in Islam.
-
D.
Badawi Najdi Arabic
Badawi Najdi Arabic is a Bedouin variety of the Najdi Arabic dialect spoken primarily by nomadic and tribal communities in central Arabia.
-
E.
Shami Arabic
Shami Arabic is a major colloquial variety of Arabic spoken across the Levant, including Syria, Lebanon, Jordan, Palestine, and surrounding areas.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69a889132b488190bbb43ad4780ddd92 |
completed | March 4, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69abc685f05481909c863b29d1f6bacd |
completed | March 7, 2026, 6:32 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae8979bca08190aac46ef3dc1a2be2 |
completed | March 9, 2026, 8:48 a.m. |
Created at: March 4, 2026, 7:51 p.m.