Triple
T32194121
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | New York City airspace |
E822352
|
entity |
| Predicate | nearbyOceanicEntryPoint |
P194817
|
FINISHED |
| Object | North Atlantic Tracks |
—
|
NE NERFINISHED |
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: North Atlantic Tracks | Statement: [New York City airspace, nearbyOceanicEntryPoint, North Atlantic Tracks]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nearbyOceanicEntryPoint Context triple: [New York City airspace, nearbyOceanicEntryPoint, North Atlantic Tracks]
-
A.
nearbyCityOrPort
Indicates that one location is geographically close to a city or port, typically within a short travel distance.
-
B.
nearbySeaLane
Indicates that one entity is located close to a sea lane used for maritime navigation or shipping.
-
C.
hasNearbyCoast
Indicates that one location is situated close to a coastline or seashore.
-
D.
nearbyStrait
Indicates that one entity is located close to or adjacent to a particular strait.
-
E.
nearestSea
Indicates that one location is the closest sea to a given place compared to all other seas.
- 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_69f3490819cc81909bae1f8ce99423c5 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69fd884cb2b48190b6acd473430d9e19 |
completed | May 8, 2026, 6:53 a.m. |
| PD | Predicate disambiguation | batch_69fd8709ca208190a8bab836f0156af5 |
completed | May 8, 2026, 6:47 a.m. |
| PDg | Predicate description generation | batch_69fd884b9d908190833de9500ff6d62a |
completed | May 8, 2026, 6:52 a.m. |
Created at: May 1, 2026, 12:35 a.m.