Triple
T12001350
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rimah Governorate |
E285669
|
entity |
| Predicate | capital |
P234
|
FINISHED |
| Object | Rimah |
E205238
|
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: Rimah | Statement: [Rimah Governorate, capital, Rimah]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rimah Context triple: [Rimah Governorate, capital, Rimah]
-
A.
Rimah
chosen
Rimah is a town in central Saudi Arabia situated within Riyadh Province, known for its desert environment and proximity to the capital region.
-
B.
Humera
Humera is a town in northwestern Ethiopia near the borders with Eritrea and Sudan, known for its strategic location and sesame production.
-
C.
Nawbahar
Nawbahar was the mother of Mahmud of Ghazni, the prominent 11th-century sultan who founded the Ghaznavid Empire in present-day Afghanistan and northern India.
-
D.
Alkham
Alkham is a rural village and civil parish in Kent, England, situated in a valley between Dover and Folkestone.
-
E.
Mir-e Bakhshi
Mir-e Bakhshi was a high-ranking Mughal imperial official responsible for military administration, including the management of army personnel and pay.
- 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_69d6ab45a368819084fce08bf0dc3705 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d903c36b248190b446b17def94885b |
completed | April 10, 2026, 2:05 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f4729eb4a081909d93b3fc74509d86 |
completed | May 1, 2026, 9:30 a.m. |
Created at: April 8, 2026, 9:46 p.m.