Triple
T32763508
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ontario–New York border |
E837822
|
entity |
| Predicate | nearCityOnNewYorkSide |
P175510
|
FINISHED |
| Object | Niagara Falls, New York |
—
|
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: Niagara Falls, New York | Statement: [Ontario–New York border, nearCityOnNewYorkSide, Niagara Falls, New York]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nearCityOnNewYorkSide Context triple: [Ontario–New York border, nearCityOnNewYorkSide, Niagara Falls, New York]
-
A.
locatedInDirectionFromNYC
Indicates that one place is situated in a specified compass direction relative to New York City.
-
B.
nearCityOnOntarioSide
Indicates that one entity is located close to a city that lies on the Ontario side of a border or region.
-
C.
onSideOfManhattan
Indicates that one entity is located on the same side of Manhattan as, or relative to, another reference entity.
-
D.
adjacentStationTowardNYC
Indicates that one station is directly next to another in the direction toward New York City.
-
E.
hasNearbyBorough
Indicates that one borough is geographically close to or adjacent to another borough.
- 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_69f34939857c8190aa9970c51feec1eb |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6d210fc80819091ed8961aa2cddfb |
completed | May 3, 2026, 4:41 a.m. |
| PD | Predicate disambiguation | batch_69f6cfe45554819089cbbd538d992132 |
completed | May 3, 2026, 4:32 a.m. |
| PDg | Predicate description generation | batch_69f6d16b79dc8190ab0d4657f2ef9a5b |
completed | May 3, 2026, 4:39 a.m. |
Created at: May 1, 2026, 1:13 a.m.