Triple
T6319893
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Okryu Bridge |
E141710
|
entity |
| Predicate | roleInCityscape |
P8652
|
FINISHED |
| Object | prominent feature of Taedong River waterfront |
—
|
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: prominent feature of Taedong River waterfront | Statement: [Okryu Bridge, roleInCityscape, prominent feature of Taedong River waterfront]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roleInCityscape Context triple: [Okryu Bridge, roleInCityscape, prominent feature of Taedong River waterfront]
-
A.
roleInUrbanPlan
Indicates the specific function, responsibility, or position an entity holds within an urban planning context or scheme.
-
B.
roleAsPlace
Indicates that an entity functions or is used as a place or location in relation to another entity or event.
-
C.
hasCityRole
Indicates that an entity holds or is assigned a specific role, function, or status within a particular city.
-
D.
urbanRole
chosen
Indicates the function, status, or role that an entity holds within an urban or city context.
-
E.
roleInScene
Indicates that an entity participates in a particular scene with a specific role or function within that scene.
- 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_69c008d13b8c8190be47d896eb735605 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c064c4ed7c8190bd066dc7cd3d1329 |
completed | March 22, 2026, 9:53 p.m. |
| PD | Predicate disambiguation | batch_69c060e5efc48190861b8266e5b0cc0c |
completed | March 22, 2026, 9:36 p.m. |
Created at: March 22, 2026, 4:29 p.m.