Triple
T8160732
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Logan Pass |
E190570
|
entity |
| Predicate | parkingOften |
P81029
|
FINISHED |
| Object | crowded in peak season |
—
|
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: crowded in peak season | Statement: [Logan Pass, parkingOften, crowded in peak season]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: parkingOften Context triple: [Logan Pass, parkingOften, crowded in peak season]
-
A.
hasParkingNearby
Indicates that a location has one or more parking facilities or spaces available within a close surrounding area.
-
B.
parkServed
Indicates that a particular park is provided with services or coverage by a specified entity (such as a transit line, facility, or administrative body).
-
C.
parkingType
Indicates the specific kind or category of parking arrangement associated with an entity (e.g., street, garage, lot, reserved).
-
D.
parkingRequirement
Indicates the specified conditions or obligations related to providing or using parking associated with an entity or activity.
-
E.
hasParking
Indicates that a place or facility provides designated parking space(s) available for use.
- 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_69ca82bfeb6481909d07b91b5cf69f59 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb455559188190bf95d9d93bb76002 |
completed | March 31, 2026, 3:53 a.m. |
| PD | Predicate disambiguation | batch_69cb36a4c40c81909f60aef0e1624c13 |
completed | March 31, 2026, 2:51 a.m. |
| PDg | Predicate description generation | batch_69cb40a017608190b6b48cf60335fa8d |
completed | March 31, 2026, 3:33 a.m. |
Created at: March 30, 2026, 5:38 p.m.