Triple
T3030730
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nabatieh |
E82886
|
entity |
| Predicate | languageUsed |
P238
|
FINISHED |
| Object | Arabic |
E1330
|
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: Arabic | Statement: [Nabatieh, languageUsed, Arabic]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Arabic Context triple: [Nabatieh, languageUsed, Arabic]
-
A.
Arabic
chosen
Arabic is a Semitic language widely spoken across the Arab world and used as a liturgical language in Islam.
-
B.
Hijazi Arabic
Hijazi Arabic is a major regional variety of Arabic spoken primarily in western Saudi Arabia, especially in the Hijaz region including cities like Mecca, Medina, and Jeddah.
-
C.
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.
-
D.
Hassaniya Arabic
Hassaniya Arabic is a variety of Arabic spoken primarily in Mauritania and parts of neighboring West African and Saharan countries, known for its Bedouin roots and distinctive phonology and vocabulary.
-
E.
Egyptian Arabic
Egyptian Arabic is the most widely understood modern Arabic dialect, centered in Egypt and heavily influenced by the speech and media of Cairo.
- 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_69ad8b21a62881908ec5dd4fba4a187c |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad9aee2fec81908116939a8d773fc4 |
completed | March 8, 2026, 3:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b1deb6dc8c8190a5714894b9ca24a1 |
completed | March 11, 2026, 9:29 p.m. |
Created at: March 8, 2026, 3:01 p.m.