Triple
T611430
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yemeni Arabic |
E12107
|
entity |
| Predicate | hasDialects |
P4251
|
FINISHED |
| Object |
Tihami Arabic
Tihami Arabic is a regional variety of Arabic spoken along Yemen’s Red Sea coastal plain, distinguished by its unique phonological and lexical features within the broader Yemeni Arabic continuum.
|
E76697
|
NE FINISHED |
How this triple was built (4 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: Tihami Arabic | Statement: [Yemeni Arabic, hasDialects, Tihami Arabic]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tihami Arabic Context triple: [Yemeni Arabic, hasDialects, Tihami Arabic]
-
A.
Shami Arabic
Shami Arabic is a major colloquial variety of Arabic spoken across the Levant, including Syria, Lebanon, Jordan, Palestine, and surrounding areas.
-
B.
Hanan
Hanan is a given name most notably borne by Palestinian legislator, activist, and scholar Hanan Ashrawi.
-
C.
Ashrawi
Ashrawi is the surname of Hanan Ashrawi, a prominent Palestinian legislator, activist, and academic.
-
D.
Khaldoon
Khaldoon is an Arabic masculine given name commonly used in the Middle East.
-
E.
Amr
Amr is a common Arabic male given name, often associated with historical and contemporary figures across the Arab world.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Tihami Arabic Triple: [Yemeni Arabic, hasDialects, Tihami Arabic]
Generated description
Tihami Arabic is a regional variety of Arabic spoken along Yemen’s Red Sea coastal plain, distinguished by its unique phonological and lexical features within the broader Yemeni Arabic continuum.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tihami Arabic Target entity description: Tihami Arabic is a regional variety of Arabic spoken along Yemen’s Red Sea coastal plain, distinguished by its unique phonological and lexical features within the broader Yemeni Arabic continuum.
-
A.
Shami Arabic
Shami Arabic is a major colloquial variety of Arabic spoken across the Levant, including Syria, Lebanon, Jordan, Palestine, and surrounding areas.
-
B.
Hanan
Hanan is a given name most notably borne by Palestinian legislator, activist, and scholar Hanan Ashrawi.
-
C.
Ashrawi
Ashrawi is the surname of Hanan Ashrawi, a prominent Palestinian legislator, activist, and academic.
-
D.
Khaldoon
Khaldoon is an Arabic masculine given name commonly used in the Middle East.
-
E.
Amr
Amr is a common Arabic male given name, often associated with historical and contemporary figures across the Arab world.
- F. None of above. chosen
Provenance (5 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_69a493309df48190a327f748e88049a6 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49df7c088819082eb70de4f0f4fbf |
completed | March 1, 2026, 8:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a533cc0c408190afc136a07b55a7a1 |
completed | March 2, 2026, 6:53 a.m. |
| NEDg | Description generation | batch_69a550cf2a64819081b56ab0fd2d5579 |
completed | March 2, 2026, 8:56 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69a5513340c48190bbf9855895fa356f |
completed | March 2, 2026, 8:58 a.m. |
Created at: March 1, 2026, 7:35 p.m.