Triple
T596358
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Davis station |
E17390
|
entity |
| Predicate | hasVendingMachines |
P12416
|
FINISHED |
| Object | ticket vending machines |
—
|
LITERAL 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: ticket vending machines | Statement: [Davis station, hasVendingMachines, ticket vending machines]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasVendingMachines Context triple: [Davis station, hasVendingMachines, ticket vending machines]
-
A.
canBePurchasedWith
Indicates that one entity is able to be bought or acquired using another entity as the form of payment.
-
B.
hasRetailFormat
Indicates that one entity operates or is organized according to a particular retail format or store type.
-
C.
isServedAt
Indicates that something (such as food, drink, or a service) is provided or made available at a particular place or venue.
-
D.
hasFacilities
chosen
Indicates that an entity possesses, provides, or is equipped with certain facilities or physical resources.
-
E.
hasVIPTerminal
Indicates that one entity possesses or provides access to a VIP (very important person) terminal associated with another entity.
- F. None of above.
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_69a49379d09c8190ac7e00b24e2810b1 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a49bd3e5e08190be95cb2009aad42d |
completed | March 1, 2026, 8:04 p.m. |
| PD | Predicate disambiguation | batch_69a494cfb52c81908d816a4c5579c321 |
completed | March 1, 2026, 7:34 p.m. |
Created at: March 1, 2026, 7:33 p.m.