Triple
T7856457
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Benazir Bhutto International Airport |
E182386
|
entity |
| Predicate | hadCargoFacilities |
P2420
|
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: [Benazir Bhutto International Airport, hadCargoFacilities, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hadCargoFacilities Context triple: [Benazir Bhutto International Airport, hadCargoFacilities, yes]
-
A.
hasCargoTerminal
chosen
Indicates that a location or facility includes or is equipped with a cargo terminal for handling freight.
-
B.
hasCargoServices
Indicates that an entity provides or is equipped to handle cargo transportation or freight services for another entity or location.
-
C.
hasFreightFacility
Indicates that an entity is equipped with or connected to a facility used for handling, loading, unloading, or storing freight.
-
D.
hasRailFacility
Indicates that an entity possesses or is served by a rail-related facility, such as a railway station, terminal, or yard.
-
E.
hasCargoDivision
Indicates that an organization possesses a specific division or unit responsible for cargo-related operations or services.
- 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_69ca82887fd48190975896bf38c4596b |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb1a75de548190af5653409a3b3881 |
completed | March 31, 2026, 12:51 a.m. |
| PD | Predicate disambiguation | batch_69cae92180f88190ae3d44c3de7adc93 |
completed | March 30, 2026, 9:20 p.m. |
Created at: March 30, 2026, 4:52 p.m.