Triple
T27012829
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dong-gu, Daegu |
E680438
|
entity |
| Predicate | mobileCountryCode |
P161773
|
FINISHED |
| Object | 450 (South Korea) |
—
|
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: 450 (South Korea) | Statement: [Dong-gu, Daegu, mobileCountryCode, 450 (South Korea)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mobileCountryCode Context triple: [Dong-gu, Daegu, mobileCountryCode, 450 (South Korea)]
-
A.
continentCode
Indicates the standardized code assigned to the continent with which an entity is associated.
-
B.
numericCountryCode
Indicates that a country is associated with a specific numeric code that uniquely identifies it.
-
C.
telecommunicationsRegulatorOfCountry
Indicates that an entity serves as the official telecommunications regulatory authority for a given country.
-
D.
associatedCountryCode
Indicates that there is a relationship linking something to the country identified by the given country code.
-
E.
UICCountryCode
Indicates that an entity is associated with a specific country identified by its UIC (International Union of Railways) country code.
- 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_69eeeb53939c8190bd431f32b060f01f |
completed | April 27, 2026, 4:51 a.m. |
| NER | Named-entity recognition | batch_69f621fd9e148190ad88ea06663957f8 |
completed | May 2, 2026, 4:10 p.m. |
| PD | Predicate disambiguation | batch_69f61b3ee7b08190a0a1bc5d26b757aa |
completed | May 2, 2026, 3:41 p.m. |
| PDg | Predicate description generation | batch_69f61f109ef48190873bfe18638d2046 |
completed | May 2, 2026, 3:58 p.m. |
Created at: April 27, 2026, 7:04 a.m.