Triple
T3085049
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Noida International Airport |
E64350
|
entity |
| Predicate | cargoTerminalPlanned |
P45778
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Noida International Airport, cargoTerminalPlanned, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cargoTerminalPlanned Context triple: [Noida International Airport, cargoTerminalPlanned, yes]
-
A.
hasCargoTerminal
Indicates that a location or facility includes or is equipped with a cargo terminal for handling freight.
-
B.
cargoLoading
Indicates the action or process of placing cargo onto a vehicle, vessel, or other transport medium for shipment or movement.
-
C.
servesAsCargoHubFor
Indicates that one entity functions as a central location or facility for handling, consolidating, and distributing cargo associated with another entity.
-
D.
freightTraffic
Indicates the movement or volume of goods and cargo being transported, typically via commercial transport networks such as rail, road, sea, or air.
-
E.
hasPassengerTerminal
Indicates that one entity possesses or is equipped with a passenger terminal used for boarding, alighting, or handling passengers.
- 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_69ad857bb4c88190a4cf27893fcabed8 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada1e98a1c8190b1dd4a0a47f7d6c6 |
completed | March 8, 2026, 4:20 p.m. |
| PD | Predicate disambiguation | batch_69ad9debb6308190be28378ae1fc98af |
completed | March 8, 2026, 4:03 p.m. |
| PDg | Predicate description generation | batch_69ada0f6fef48190b13898be383a246b |
completed | March 8, 2026, 4:16 p.m. |
Created at: March 8, 2026, 3:03 p.m.