Triple
T8525624
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 북구 |
E201807
|
entity |
| Predicate | isDirectionalDistrictName |
P83149
|
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: [북구, isDirectionalDistrictName, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isDirectionalDistrictName Context triple: [북구, isDirectionalDistrictName, true]
-
A.
hasStreetDirection
Indicates that a street or road segment is associated with a specific directional orientation (e.g., northbound, east-west).
-
B.
directionalDesignation
Indicates a relationship where one entity is assigned or labeled with a specific directional orientation relative to another entity or reference frame.
-
C.
geographicDirectionWithinCountry
Indicates that one place lies in a specified cardinal or intercardinal direction relative to another place within the same country.
-
D.
containsDirectionOf
Indicates that one entity includes or encompasses the directional orientation or path associated with another entity.
-
E.
isUrbanDistrict
Indicates that a given district is classified as an urban administrative or residential area rather than a rural one.
- 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_69ca83228b24819085d22e7dc99f5d94 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe6463fe48190b6d3482212356be1 |
completed | March 31, 2026, 3:20 p.m. |
| PD | Predicate disambiguation | batch_69cbd10f64b4819080859057c19e58f0 |
completed | March 31, 2026, 1:50 p.m. |
| PDg | Predicate description generation | batch_69cbe30d453481908f897ed2b06e7534 |
completed | March 31, 2026, 3:06 p.m. |
Created at: March 30, 2026, 6:16 p.m.