Triple
T7163427
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | South Arabian script |
E167003
|
entity |
| Predicate | region |
P40
|
FINISHED |
| Object | Oman |
E19046
|
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: Oman | Statement: [South Arabian script, region, Oman]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Oman Context triple: [South Arabian script, region, Oman]
-
A.
Oman
chosen
Oman is a Middle Eastern country on the southeastern coast of the Arabian Peninsula, known for its historic trading ports, desert and mountain landscapes, and stable, oil-based economy.
-
B.
Bahrain
Bahrain is a small island nation in the Persian Gulf known for its rich history, oil wealth, and status as a regional financial and cultural hub.
-
C.
Bahrain
Bahrain is a popular riverside town and tourist destination in Pakistan’s Swat Valley, known for its scenic beauty and as a base for exploring nearby mountain areas.
-
D.
Dhofar
Dhofar is a coastal and mountainous region in southwestern Oman known for its monsoon climate, frankincense production, and historical role in Arabian trade routes.
-
E.
Sulaymaniya
Sulaymaniya is a sub-school within the Zaydi branch of Shia Islam, distinguished by its own specific theological and legal interpretations.
- 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_69c68888c10c819095e0383020225758 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e82feee481908fa180ea8c9924fa |
completed | March 27, 2026, 8:27 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7adc8b06c81909791e38becb594f6 |
completed | March 28, 2026, 10:30 a.m. |
Created at: March 27, 2026, 2:47 p.m.