Triple
T29977
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Heavenly Mountain Resort |
E598
|
entity |
| Predicate | hasAccommodationNearby |
P105
|
FINISHED |
| Object | hotels in South Lake Tahoe |
—
|
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: hotels in South Lake Tahoe | Statement: [Heavenly Mountain Resort, hasAccommodationNearby, hotels in South Lake Tahoe]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAccommodationNearby Context triple: [Heavenly Mountain Resort, hasAccommodationNearby, hotels in South Lake Tahoe]
-
A.
near
Indicates that one entity is located at a short distance from another entity in space or position.
-
B.
hostsEvent
Indicates that an entity organizes and provides the venue or setting for an event to take place.
-
C.
hasParkAlongBank
Indicates that a park is located adjacent to or running alongside the bank of a water body.
-
D.
isTouristDestination
Indicates that a place is recognized as a location people commonly visit for leisure, sightseeing, or travel.
-
E.
hasNotableFacility
chosen
Indicates that an entity possesses or hosts a facility that is of particular significance, prominence, or interest.
- 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_69a2479dec388190967ba648663442c9 |
completed | Feb. 28, 2026, 1:40 a.m. |
| NER | Named-entity recognition | batch_69a2490d80a0819083bf604c1229e903 |
completed | Feb. 28, 2026, 1:46 a.m. |
| PD | Predicate disambiguation | batch_69a2486eb01881909241540dda28e1ff |
completed | Feb. 28, 2026, 1:44 a.m. |
Created at: Feb. 28, 2026, 1:44 a.m.