Triple
T31139355
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Armoy |
E793737
|
entity |
| Predicate | hasNearbyScenicAttraction |
P3449
|
FINISHED |
| Object | Causeway Coastal Route |
—
|
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: Causeway Coastal Route | Statement: [Armoy, hasNearbyScenicAttraction, Causeway Coastal Route]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNearbyScenicAttraction Context triple: [Armoy, hasNearbyScenicAttraction, Causeway Coastal Route]
-
A.
hasAttractionNearby
chosen
Indicates that one entity is located close to another entity that serves as an attraction or point of interest.
-
B.
hasScenicSectionNear
Indicates that one location includes a visually appealing or picturesque segment situated close to another specified location.
-
C.
hasScenicPassNearby
Indicates that a location is situated close to a notable scenic pass, such as a mountain or landscape viewpoint route.
-
D.
hasNearbyStatePark
Indicates that a location is situated close to at least one designated state park.
-
E.
hasRecreationalActivityNearby
Indicates that a location has one or more recreational activities or facilities available in its nearby surroundings.
- 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_69f224d2b3a48190aa9dd26fbf6eab1a |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69fed6da0390819096b88ef4714b144e |
completed | May 9, 2026, 6:40 a.m. |
| PD | Predicate disambiguation | batch_69fed53517d081909966f31707625f1a |
completed | May 9, 2026, 6:33 a.m. |
Created at: April 29, 2026, 9:05 p.m.