Triple
T22677127
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yonggwang Station |
E560371
|
entity |
| Predicate | notableForTourists |
P35273
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Yonggwang Station, notableForTourists, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableForTourists Context triple: [Yonggwang Station, notableForTourists, yes]
-
A.
notablePlace
Indicates that a place is especially significant, famous, or noteworthy in relation to the subject.
-
B.
notableSpot
Indicates that a location is recognized as a significant or noteworthy place in some context.
-
C.
notableDestination
chosen
Indicates that a location is recognized as a significant or prominent place that people commonly travel to or aim to visit.
-
D.
alsoAttractsTouristsIn
Indicates that a place, in addition to another, draws or appeals to tourists within a specified location or context.
-
E.
notableInCity
Indicates that an entity is particularly prominent, recognized, or significant within a specific city.
- 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_69e2454bfd00819099115715a22cb057 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f1785d93e48190b37d11642b0cb123 |
completed | April 29, 2026, 3:17 a.m. |
| PD | Predicate disambiguation | batch_69ee62a6245881909506ff502da14137 |
completed | April 26, 2026, 7:08 p.m. |
Created at: April 17, 2026, 3:11 p.m.