Triple
T20776852
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sangin District |
E511376
|
entity |
| Predicate | capital |
P234
|
FINISHED |
| Object | Sangin |
—
|
NE NERFINISHED |
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: Sangin | Statement: [Sangin District, capital, Sangin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sangin Context triple: [Sangin District, capital, Sangin]
-
A.
Sangin
chosen
Sangin is a town in southern Afghanistan that gained notoriety as a major battleground during the Afghan conflict, particularly involving British and U.S. forces.
-
B.
Sabahi
Sabahi is the surname of Egyptian politician and activist Hamdeen Sabahi, known for his Nasserist views and presidential campaigns.
-
C.
Rano
Rano is a historic town and traditional emirate in northern Nigeria, located within Kano State.
-
D.
Rano
Rano is a dialect of the Uripiv-Wala-Rano-Atchin language cluster spoken in Vanuatu.
-
E.
Besisahar
Besisahar is a town in Nepal’s Lamjung District that serves as a key gateway and transport hub for popular Himalayan trekking routes.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b4cac7a48190a715cb3d545df2b4 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c26bbe108190bb7c3e5b416e44fe |
completed | April 21, 2026, 12:18 a.m. |
Created at: April 16, 2026, 12:37 p.m.