Triple
T20023270
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | IR |
E494913
|
entity |
| Predicate | ticketingCategory |
P138405
|
FINISHED |
| Object | long-distance tariff in many countries |
—
|
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: long-distance tariff in many countries | Statement: [IR, ticketingCategory, long-distance tariff in many countries]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ticketingCategory Context triple: [IR, ticketingCategory, long-distance tariff in many countries]
-
A.
ticketingScope
Indicates the range or domain within which ticketing actions (such as creation, assignment, or management of tickets) are valid or applicable.
-
B.
ticketClass
Indicates the category or level of service assigned to a ticket within a ticketing or reservation system.
-
C.
ticketingProduct
Indicates a relationship where an entity is associated with, or offered as, a ticketing-related product (such as a service or item used for issuing, managing, or selling tickets).
-
D.
ticketClassSystem
Indicates that an entity is classified within a particular ticketing or fare class system that defines categories or levels of tickets.
-
E.
ticketingZoneType
Indicates the type or category of ticketing zone that applies within a given area or context.
- 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_69da626bfd288190aa5d65098b6433ae |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e6628a1ecc8190bf6ee0bedb61e0b8 |
completed | April 20, 2026, 5:29 p.m. |
| PD | Predicate disambiguation | batch_69e54ce752748190a0a1ffddd0372271 |
completed | April 19, 2026, 9:45 p.m. |
| PDg | Predicate description generation | batch_69e54fc20888819083c9118a09d0d2dc |
completed | April 19, 2026, 9:57 p.m. |
Created at: April 11, 2026, 3:35 p.m.