Triple
T14743922
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Y class |
E346417
|
entity |
| Predicate | bookingCodeLetter |
P115602
|
FINISHED |
| Object | Y |
—
|
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: Y | Statement: [Y class, bookingCodeLetter, Y]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: bookingCodeLetter Context triple: [Y class, bookingCodeLetter, Y]
-
A.
bookingCodeType
Indicates the type or category of a booking code used to classify or identify a reservation.
-
B.
ticketingCode
Indicates the specific fare or booking code associated with a ticket that defines its pricing, rules, and conditions of use.
-
C.
IATAcode
Indicates the three-letter IATA airport or airline code assigned to the entity.
-
D.
hasIATAcode
Indicates that an entity, typically a transportation facility like an airport, is associated with a specific IATA (International Air Transport Association) code.
-
E.
taxiPackageCode
Indicates that a specific package or service option is associated with a taxi ride, identified by a particular code.
- 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_69d822e6f1c88190bc494d491a907114 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69dec7367a1c819081082cc355e385fa |
completed | April 14, 2026, 11:01 p.m. |
| PD | Predicate disambiguation | batch_69de8bf9331481909582045cd567d91f |
completed | April 14, 2026, 6:48 p.m. |
| PDg | Predicate description generation | batch_69de8f4b67cc8190b84b59fcec5cf579 |
completed | April 14, 2026, 7:02 p.m. |
Created at: April 10, 2026, 1:30 a.m.