Triple
T632004
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Islamic world |
E15944
|
entity |
| Predicate | hasCulturalCenter |
P2412
|
FINISHED |
| Object | Muscat |
E15312
|
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: Muscat | Statement: [Islamic world, hasCulturalCenter, Muscat]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Muscat Context triple: [Islamic world, hasCulturalCenter, Muscat]
-
A.
Muscat
chosen
Muscat is the capital and largest city of Oman, known for its historic port, white-washed architecture, and strategic location on the Gulf of Oman.
-
B.
Sanaʽa
Sanaʽa is the historic capital and one of the largest cities of Yemen, renowned for its ancient architecture and cultural significance in the Arabian Peninsula.
-
C.
Aden
Aden is a strategic port city in Yemen located on the Gulf of Aden, historically significant as a major maritime hub and former British colonial stronghold.
-
D.
Manama
Manama is the capital and largest city of Bahrain, serving as a key financial and commercial hub in the Persian Gulf region.
-
E.
Sharjah
Sharjah is a major cultural and economic center in the United Arab Emirates, known for its rich heritage, museums, and role as a hub of Islamic arts and education.
- 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_69a4935c131c8190a5378c6bf101e8cc |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a49ec2a4c08190bc5c6ce8a10b0967 |
completed | March 1, 2026, 8:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a64a4ba2d88190969e7c777a1bbfd7 |
completed | March 3, 2026, 2:41 a.m. |
Created at: March 1, 2026, 7:35 p.m.