Triple
T2864032
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | EWR |
E63393
|
entity |
| Predicate | rankInNYCAreaByTraffic |
P42802
|
FINISHED |
| Object | one of the three major airports |
—
|
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: one of the three major airports | Statement: [EWR, rankInNYCAreaByTraffic, one of the three major airports]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rankInNYCAreaByTraffic Context triple: [EWR, rankInNYCAreaByTraffic, one of the three major airports]
-
A.
passengerTrafficRankUS
Indicates the relative ranking of a location or facility within the United States based on the volume of passenger traffic it handles.
-
B.
hasCommuterTraffic
Indicates that there is regular, recurring traffic flow associated with people traveling between their homes and places of work or study.
-
C.
roadTraffic
Indicates the presence, flow, or conditions of vehicles and movement along roads or streets.
-
D.
trafficDirection
Indicates the direction in which traffic is intended or allowed to move relative to a given reference point or segment.
-
E.
nearbyTransit
Indicates that one location has public transportation options situated within a short distance or easy access from it.
- 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_69ab4c42fb8c8190b36e161d47c03b81 |
completed | March 6, 2026, 9:50 p.m. |
| NER | Named-entity recognition | batch_69abdfb853908190aa2fd492e9fa5e87 |
completed | March 7, 2026, 8:20 a.m. |
| PD | Predicate disambiguation | batch_69abdd123ec48190af50a1859aea50b7 |
completed | March 7, 2026, 8:08 a.m. |
| PDg | Predicate description generation | batch_69abddedd72c819094a9c4161af07780 |
completed | March 7, 2026, 8:12 a.m. |
Created at: March 6, 2026, 10:02 p.m.