Triple
T20892500
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hanseong |
E514441
|
entity |
| Predicate | successorName |
P78
|
FINISHED |
| Object | Seoul (current name) |
—
|
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: Seoul (current name) | Statement: [Hanseong, successorName, Seoul (current name)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Seoul (current name) Context triple: [Hanseong, successorName, Seoul (current name)]
-
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.
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.
-
C.
Sejong City
Sejong City is South Korea’s planned administrative capital, designed to house numerous government ministries and ease congestion in Seoul.
-
D.
Kangbuk-gu, Seoul
Kangbuk-gu, Seoul is a northern district of South Korea’s capital city known for its residential neighborhoods, mountainous landscapes, and cultural sites.
-
E.
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.
- 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_69e0b4f7ebe48190952a85547a0f31a1 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6d05f0bec8190a296db546bd34114 |
completed | April 21, 2026, 1:18 a.m. |
Created at: April 16, 2026, 12:46 p.m.