Triple
T10681455
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pesa |
E251764
|
entity |
| Predicate | hasBrand |
P1500
|
FINISHED |
| Object | Pesa Link |
E251764
|
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: Pesa Link | Statement: [Pesa, hasBrand, Pesa Link]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pesa Link Context triple: [Pesa, hasBrand, Pesa Link]
-
A.
Pesa
The Pesa is a river in Tuscany, central Italy, known for flowing through the Chianti region before joining the Arno.
-
B.
Pesa
chosen
Pesa is a Polish manufacturer of rail vehicles, particularly known for producing modern trams and trains used in various European cities.
-
C.
PiTaPa
PiTaPa is a rechargeable contactless smart card system used for fare payment on public transportation networks in the Kansai region of Japan.
-
D.
Silverlink Metro
Silverlink Metro was a former suburban rail network in London and surrounding areas that operated under the Silverlink franchise until its services were absorbed into the London Overground.
-
E.
GoPay
GoPay is a leading Indonesian digital wallet and payment platform that enables users to make cashless transactions for online and offline services, including ride-hailing, food delivery, and bill payments.
- 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_69d6aa5bd7c08190a816e733b4045c23 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d6fcc30be481909922844b539b622d |
completed | April 9, 2026, 1:11 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d98885abf88190b54ed9db779d3ff0 |
completed | April 10, 2026, 11:32 p.m. |
Created at: April 8, 2026, 9:10 p.m.