Triple
T8975165
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Newark Bay Bridge |
E214368
|
entity |
| Predicate | roadwayCount |
P28807
|
FINISHED |
| Object | 2 carriageways |
—
|
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: 2 carriageways | Statement: [Newark Bay Bridge, roadwayCount, 2 carriageways]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roadwayCount Context triple: [Newark Bay Bridge, roadwayCount, 2 carriageways]
-
A.
numberOfRoadways
chosen
Indicates the count of distinct roadways associated with or present at a given entity or location.
-
B.
laneCount
Indicates the number of parallel lanes associated with a given road or roadway segment.
-
C.
hasRoadway
Indicates that one location or area is connected to another by a road or roadway infrastructure.
-
D.
roadSystem
Indicates a relationship where multiple roads are organized and connected as part of a larger, integrated transportation network or infrastructure.
-
E.
numberOfConvergingStreets
Indicates the count of distinct streets that meet or intersect at a particular junction or location.
- 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_69ca839dbf608190a2f5990477115d29 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc6784d1808190899c980f76084ff8 |
completed | April 1, 2026, 12:32 a.m. |
| PD | Predicate disambiguation | batch_69cc5ed9a2d48190ad11381078e823b7 |
completed | March 31, 2026, 11:55 p.m. |
Created at: March 30, 2026, 7:02 p.m.