Triple
T9460790
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sarikoli |
E228138
|
entity |
| Predicate | closelyRelatedTo |
P37
|
FINISHED |
| Object | Shughni |
E230685
|
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: Shughni | Statement: [Sarikoli, closelyRelatedTo, Shughni]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Shughni Context triple: [Sarikoli, closelyRelatedTo, Shughni]
-
A.
Shughni
chosen
Shughni is an Eastern Iranian language spoken primarily in the Badakhshan region of Tajikistan and Afghanistan, known for its use among the Shughni people in the Pamir Mountains.
-
B.
Khashuri
Khashuri is a town in central Georgia that serves as an important regional transport hub and gateway between eastern and western parts of the country.
-
C.
Barya
Barya is an alternative name for the Nara people, an ethnic group primarily inhabiting parts of Eritrea.
-
D.
Shushary
Shushary is a municipal settlement in the southern part of Saint Petersburg, Russia, known for its residential areas and industrial facilities.
-
E.
Tayshet
Tayshet is a town in Irkutsk Oblast, Russia, known as a major railway junction in Siberia.
- 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_69ca843b123881909b0e60028475d12d |
completed | March 30, 2026, 2:10 p.m. |
| NER | Named-entity recognition | batch_69cd7fcaf610819092bcd3b871665aa5 |
completed | April 1, 2026, 8:27 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d12ce01b548190a30f6cc7f3084b06 |
completed | April 4, 2026, 3:23 p.m. |
Created at: March 30, 2026, 7:52 p.m.