Triple
T25417101
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hwangnyeongsan |
E636866
|
entity |
| Predicate | isUrbanMountain |
P158279
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Hwangnyeongsan, isUrbanMountain, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isUrbanMountain Context triple: [Hwangnyeongsan, isUrbanMountain, true]
-
A.
isUrbanTrail
Indicates that a given trail is located within or primarily passes through an urban or developed area.
-
B.
isUrbanRiding
Indicates that an entity is engaged in riding (such as cycling, motorcycling, or similar transport) specifically within an urban or city environment.
-
C.
isUrbanForm
Indicates that an entity represents or exhibits characteristics of an urban built environment or city-like spatial structure.
-
D.
hasMountainSport
Indicates that an entity is associated with or offers a particular mountain-related sport or activity.
-
E.
isUrbanNode
Indicates that a location or entity functions as an urban center or node within a city or metropolitan network.
- F. None of above. chosen
Provenance (4 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_69e75db4135881909acc287ebcb7a505 |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f5b0129c648190b6afbe55d574b574 |
completed | May 2, 2026, 8:04 a.m. |
| PD | Predicate disambiguation | batch_69f45d0dbc8c8190beecce679fce90a4 |
completed | May 1, 2026, 7:58 a.m. |
| PDg | Predicate description generation | batch_69f464ae42e88190b3549fdf4e0b425e |
completed | May 1, 2026, 8:30 a.m. |
Created at: April 21, 2026, 1:55 p.m.