Triple
T36621451
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Corkscrew area |
E904049
|
entity |
| Predicate | hasNearbyAttractions |
P3449
|
FINISHED |
| Object | nearby rides and attractions |
—
|
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: nearby rides and attractions | Statement: [Corkscrew area, hasNearbyAttractions, nearby rides and attractions]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNearbyAttractions Context triple: [Corkscrew area, hasNearbyAttractions, nearby rides and attractions]
-
A.
hasAttractionNearby
chosen
Indicates that one entity is located close to another entity that serves as an attraction or point of interest.
-
B.
hasNearbyEntertainmentDistrict
Indicates that one location is situated close enough to another area known for entertainment venues (such as bars, theaters, or nightlife) to be considered nearby.
-
C.
hasRecreationalActivityNearby
Indicates that a location has one or more recreational activities or facilities available in its nearby surroundings.
-
D.
nearbyActivityHub
Indicates that one entity is located close enough to another entity that serves as a central hub or focal point for activities or events.
-
E.
nearestTouristDestination
Indicates that one location is the closest tourist destination to another specified 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_69f76e6ae750819096911e6e2d4d12c5 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_6a0061454944819088a0babfe60f69fc |
completed | May 10, 2026, 10:43 a.m. |
| PD | Predicate disambiguation | batch_6a0060b9ee108190b91e8d99a16f2b30 |
completed | May 10, 2026, 10:40 a.m. |
Created at: May 3, 2026, 4:11 p.m.