Triple
T19449517
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Seoul Plaza |
E486576
|
entity |
| Predicate | ownedBy |
P347
|
FINISHED |
| Object | City of Seoul |
—
|
NE NERFINISHED |
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: City of Seoul | Statement: [Seoul Plaza, ownedBy, City of Seoul]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: City of Seoul Context triple: [Seoul Plaza, ownedBy, City of Seoul]
-
A.
Seoul
chosen
Seoul is the capital and largest metropolis of South Korea, known as a major global center for technology, culture, and finance.
-
B.
Sejong City
Sejong City is South Korea’s planned administrative capital, designed to house numerous government ministries and ease congestion in Seoul.
-
C.
Jung-gu, Seoul
Jung-gu, Seoul is a central district of South Korea’s capital city, known for its major commercial areas, historic sites, and key government and business institutions.
-
D.
Yongin
Yongin is a rapidly growing city in the Seoul Capital Area of South Korea, known for attractions like Everland Resort and the Korean Folk Village.
-
E.
Seongnam-si
Seongnam-si is a major satellite city of Seoul in South Korea, known for its large residential districts and proximity to the capital’s economic and transportation hubs.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8e8d7ad488190a3373045029b0f3b |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e6338caeb48190aeb1d511996984e3 |
completed | April 20, 2026, 2:09 p.m. |
Created at: April 10, 2026, 1:38 p.m.