Triple
T4731335
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Windham Mountain |
E105014
|
entity |
| Predicate | drivingTimeFromNewYorkCity |
P59086
|
FINISHED |
| Object | approximately 2.5 to 3 hours |
—
|
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: approximately 2.5 to 3 hours | Statement: [Windham Mountain, drivingTimeFromNewYorkCity, approximately 2.5 to 3 hours]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: drivingTimeFromNewYorkCity Context triple: [Windham Mountain, drivingTimeFromNewYorkCity, approximately 2.5 to 3 hours]
-
A.
distanceToNewYorkCity
Indicates the spatial distance between a given entity’s location and New York City.
-
B.
distanceFromGrandCentral
Indicates the spatial distance between a given entity and Grand Central.
-
C.
drivingTimeFromSydney
Indicates the amount of time it takes to drive from Sydney to a specified location.
-
D.
distanceToPoughkeepsie
Indicates the spatial distance between a given entity and the location of Poughkeepsie.
-
E.
distanceFromPennStation
Indicates the physical distance between a given location and Penn Station.
- 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_69bd43ee52048190b81a4f066534ffb3 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd67c9c3c08190a6c4944cdd1362a8 |
completed | March 20, 2026, 3:29 p.m. |
| PD | Predicate disambiguation | batch_69bd6220071881909670c89d072ffb6d |
completed | March 20, 2026, 3:05 p.m. |
| PDg | Predicate description generation | batch_69bd67c895dc8190ba648002ff54424b |
completed | March 20, 2026, 3:29 p.m. |
Created at: March 20, 2026, 1:19 p.m.