Triple
T18024947
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Akagi mountain lakes |
E431221
|
entity |
| Predicate | arePopularFor |
P3033
|
FINISHED |
| Object | hiking |
—
|
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: hiking | Statement: [Akagi mountain lakes, arePopularFor, hiking]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: arePopularFor Context triple: [Akagi mountain lakes, arePopularFor, hiking]
-
A.
isPopularAs
Indicates that an entity is widely liked, well-known, or favored in a particular role, context, or capacity.
-
B.
isPopularAt
Indicates that an entity enjoys a high level of recognition, approval, or favor within a specified place, context, or time.
-
C.
isPopularWith
Indicates that one entity is well-liked, favored, or widely accepted by another entity or group.
-
D.
popularizedIn
Indicates that something became widely known, accepted, or fashionable within a particular place, time period, or context.
-
E.
popularFor
chosen
Indicates that something is widely liked, recognized, or favored specifically because of a particular feature, quality, or use.
- 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_69d8b9050fb48190890155145deb0a66 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4b9c554348190bd0df06d0cfe188e |
completed | April 19, 2026, 11:17 a.m. |
| PD | Predicate disambiguation | batch_69e3f904b8048190add43883cd7cb191 |
completed | April 18, 2026, 9:35 p.m. |
Created at: April 10, 2026, 10:24 a.m.