Triple
T16463480
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Abdulla Aripov |
E399868
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Aripov |
E470993
|
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: Aripov | Statement: [Abdulla Aripov, familyName, Aripov]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Aripov Context triple: [Abdulla Aripov, familyName, Aripov]
-
A.
Arapova
Arapova is a Russian-language surname historically borne by various individuals of Slavic origin.
-
B.
Arapov
chosen
Arapov is a Slavic masculine surname commonly found in Russian-speaking countries.
-
C.
Yunak
Yunak is a rural district and town in Turkey known for its agricultural economy and location within the Central Anatolia region.
-
D.
Araniko
Araniko was a renowned 13th-century Nepalese architect and artist best known for introducing Newar-style Buddhist architecture to the Yuan dynasty in China.
-
E.
Oreshek
Oreshek is the historic Russian fortress on Lake Ladoga that later gave rise to the town of Shlisselburg.
- 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_69d87f2dac988190b74d6e185fa88ba4 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e32d83687081908450657e1da6f6af |
completed | April 18, 2026, 7:06 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a004f555f6081908b1f0d524b6fb9a7 |
completed | May 10, 2026, 9:26 a.m. |
Created at: April 10, 2026, 5:10 a.m.