Triple
T29141681
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | RORS |
E738651
|
entity |
| Predicate | associatedWithFlightsAt |
P204042
|
FINISHED |
| Object | Shimojishima Airport |
E201497
|
NE 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: Shimojishima Airport | Statement: [RORS, associatedWithFlightsAt, Shimojishima Airport]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedWithFlightsAt Context triple: [RORS, associatedWithFlightsAt, Shimojishima Airport]
-
A.
associatedWithFlight
Indicates a relationship where an entity is linked or connected to a specific flight, such as by participation, operation, or relevance.
-
B.
associatedWithAirlineOperations
Indicates a relationship in which an entity is connected to, involved in, or relevant to the operations and activities of an airline.
-
C.
associatedFlightType
Indicates a relationship where one entity is linked to, or characterized by, a particular type or category of flight.
-
D.
airTravelRelationWith
Indicates a relationship where one entity travels to, from, or between locations by air (e.g., via airplane or other aircraft) in connection with another entity.
-
E.
associatedWithAirportCode
Indicates that one entity has a relationship or connection to an airport identified by a specific airport code.
- F. None of above. chosen
Provenance (5 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_69f07cb3adb48190a9e0e169cd026634 |
completed | April 28, 2026, 9:24 a.m. |
| NER | Named-entity recognition | batch_6a0311c202408190be88a85337aacf11 |
completed | May 12, 2026, 11:40 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a267e939ee88190bb3572a603b5571d |
completed | June 8, 2026, 8:34 a.m. |
| PD | Predicate disambiguation | batch_6a0310b0c9c88190ab218d47d4f432ed |
completed | May 12, 2026, 11:36 a.m. |
| PDg | Predicate description generation | batch_6a0311c145a08190ba7658db898ab7d6 |
completed | May 12, 2026, 11:40 a.m. |
Created at: April 28, 2026, 11:37 a.m.