Triple
T8363267
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Narita Airport Terminal 1 Station |
E197060
|
entity |
| Predicate | servesPassengers |
P27830
|
FINISHED |
| Object | international travelers |
—
|
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: international travelers | Statement: [Narita Airport Terminal 1 Station, servesPassengers, international travelers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: servesPassengers Context triple: [Narita Airport Terminal 1 Station, servesPassengers, international travelers]
-
A.
hasPassengerServicesTo
Indicates that a transportation provider operates passenger services connecting one location or entity to another.
-
B.
passengers
Indicates that one entity is traveling in or being transported by another entity, typically as a non-operating occupant.
-
C.
hasPassengerHandling
Indicates that an entity is responsible for or involved in managing the processes and services related to handling passengers.
-
D.
operatedPassengerServices
Indicates that an entity provided and managed transportation services specifically for carrying passengers.
-
E.
servesPassengerTrafficType
chosen
Indicates that a transportation facility or service accommodates a specified type or category of passenger traffic.
- 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_69ca82f2dbe48190aba982e75a0d94de |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb80768b208190a5f6c9e6cb6e7f30 |
completed | March 31, 2026, 8:06 a.m. |
| PD | Predicate disambiguation | batch_69cb70ca25548190b0f90c5384e3fb3c |
completed | March 31, 2026, 6:59 a.m. |
Created at: March 30, 2026, 6 p.m.