Triple
T7189984
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ING Bank Headquarters in Budapest |
E167665
|
entity |
| Predicate | occupant |
P75
|
FINISHED |
| Object | ING Bank |
E647052
|
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: ING Bank | Statement: [ING Bank Headquarters in Budapest, occupant, ING Bank]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: ING Bank Context triple: [ING Bank Headquarters in Budapest, occupant, ING Bank]
-
A.
ING Bank
chosen
ING Bank is a global Dutch financial institution offering banking, investment, and insurance services to retail and corporate clients.
-
B.
Danske Bank
Danske Bank is a major Nordic financial institution headquartered in Copenhagen, Denmark, offering a wide range of banking and financial services across Northern Europe.
-
C.
Equator Bank
Equator Bank was a financial institution where future Liberian president and economist Ellen Johnson Sirleaf held a professional position during her banking career.
-
D.
Mizuho
Mizuho is a high-speed Shinkansen train service in Japan that operates primarily between major cities such as Osaka and Kagoshima on the Sanyo and Kyushu Shinkansen lines.
-
E.
Mizuho
Mizuho is a town in Tokyo Metropolis, Japan, known for its suburban character and proximity to the Tama area.
- 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_69c6888b5248819090499a884ee3ec39 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e8ff1ad0819094761f8c73e3e986 |
completed | March 27, 2026, 8:30 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7bf903f1c819098de137c8c43ca34 |
completed | March 28, 2026, 11:46 a.m. |
Created at: March 27, 2026, 2:50 p.m.