Triple
T35583765
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | LEW |
E1028291
|
entity |
| Predicate | ticketingCodeType |
P183423
|
FINISHED |
| Object | three-letter alpha station code |
—
|
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: three-letter alpha station code | Statement: [LEW, ticketingCodeType, three-letter alpha station code]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ticketingCodeType Context triple: [LEW, ticketingCodeType, three-letter alpha station code]
-
A.
ticketingCode
Indicates the specific fare or booking code associated with a ticket that defines its pricing, rules, and conditions of use.
-
B.
bookingCodeType
Indicates the type or category of a booking code used to classify or identify a reservation.
-
C.
ticketCodeRole
Indicates a relationship where a specific ticket code is associated with a particular role or permission.
-
D.
ticketTypeExample
Indicates that an entity serves as an example or illustrative instance of a particular ticket type.
-
E.
ticketClass
Indicates the category or level of service assigned to a ticket within a ticketing or reservation system.
- F. None of above. chosen
Provenance (4 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_69f76e0495a081909beced418558c0b4 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f79f7340e4819092a1a47f7028e63f |
completed | May 3, 2026, 7:18 p.m. |
| PD | Predicate disambiguation | batch_69f79e4bdbcc8190be7a0d2cf8a77b64 |
completed | May 3, 2026, 7:13 p.m. |
| PDg | Predicate description generation | batch_69f79ec14ce08190b22cee0b40d33743 |
completed | May 3, 2026, 7:15 p.m. |
Created at: May 3, 2026, 4:04 p.m.