Triple
T2970644
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Titanic Quarter railway station |
E80270
|
entity |
| Predicate | hasTicketVendingMachine |
P3383
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Titanic Quarter railway station, hasTicketVendingMachine, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTicketVendingMachine Context triple: [Titanic Quarter railway station, hasTicketVendingMachine, yes]
-
A.
hasTicketHall
Indicates that a place or facility includes or is equipped with a designated ticket hall area for purchasing or validating tickets.
-
B.
hasTicketCollectorArea
Indicates that a location or facility includes a designated area where ticket collectors operate or perform their duties.
-
C.
hasTicketing
chosen
Indicates that an entity provides or is associated with a system or mechanism for issuing, managing, or selling tickets.
-
D.
hasVIPTerminal
Indicates that one entity possesses or provides access to a VIP (very important person) terminal associated with another entity.
-
E.
hasTicketInspection
Indicates that a ticket is checked or verified by an authorized inspector or system.
- 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_69ad8b14ffe881908ffed62f9595c867 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad997282b481909d078be0e70d9930 |
completed | March 8, 2026, 3:44 p.m. |
| PD | Predicate disambiguation | batch_69ad960e71f8819088179d11248c6ed0 |
completed | March 8, 2026, 3:30 p.m. |
Created at: March 8, 2026, 2:58 p.m.