Triple
T16568633
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mopti Region |
E402527
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Bankass
Bankass is a town and administrative center in central Mali, known for its role as a local hub within the Mopti Region.
|
E1221491
|
NE FINISHED |
How this triple was built (4 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: Bankass | Statement: [Mopti Region, contains, Bankass]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bankass Context triple: [Mopti Region, contains, Bankass]
-
A.
Girobank
Girobank was a British state-owned financial institution that provided banking and giro transfer services, originally established and run through the national postal system.
-
B.
N26
N26 is a German digital bank and fintech company offering app-based banking services across multiple European markets.
-
C.
BakiKart
BakiKart is a contactless smart card payment system used for public transportation in Baku, Azerbaijan.
-
D.
Ola Money
Ola Money is a digital wallet and payments service offered by Indian ride-hailing company Ola, enabling users to make cashless transactions for rides and other online services.
-
E.
MobilePay
MobilePay is a popular Nordic mobile payment app that allows users to send and receive money, pay in stores and online, and manage everyday transactions via their smartphones.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Bankass Triple: [Mopti Region, contains, Bankass]
Generated description
Bankass is a town and administrative center in central Mali, known for its role as a local hub within the Mopti Region.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Bankass Target entity description: Bankass is a town and administrative center in central Mali, known for its role as a local hub within the Mopti Region.
-
A.
Girobank
Girobank was a British state-owned financial institution that provided banking and giro transfer services, originally established and run through the national postal system.
-
B.
N26
N26 is a German digital bank and fintech company offering app-based banking services across multiple European markets.
-
C.
BakiKart
BakiKart is a contactless smart card payment system used for public transportation in Baku, Azerbaijan.
-
D.
Ola Money
Ola Money is a digital wallet and payments service offered by Indian ride-hailing company Ola, enabling users to make cashless transactions for rides and other online services.
-
E.
MobilePay
MobilePay is a popular Nordic mobile payment app that allows users to send and receive money, pay in stores and online, and manage everyday transactions via their smartphones.
- F. None of above. chosen
Provenance (5 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_69d8838648088190acf97ef11fc3f61b |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e35773c00c819091731bebc02a69bb |
completed | April 18, 2026, 10:05 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a006ee3dcbc819087ea66b262585232 |
completed | May 10, 2026, 11:41 a.m. |
| NEDg | Description generation | batch_6a006ff5bdb88190be90d7446e24b61f |
completed | May 10, 2026, 11:45 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a007088fd988190b3dfef081769d03e |
completed | May 10, 2026, 11:48 a.m. |
Created at: April 10, 2026, 5:16 a.m.