Triple
T20258028
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | South Chungcheong Province |
E498754
|
entity |
| Predicate | hasMajorCity |
P316
|
FINISHED |
| Object | Seosan |
—
|
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: Seosan | Statement: [South Chungcheong Province, hasMajorCity, Seosan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Seosan Context triple: [South Chungcheong Province, hasMajorCity, Seosan]
-
A.
Seosan
chosen
Seosan is a coastal city in South Chungcheong Province, South Korea, known for its agriculture, petrochemical industry, and proximity to the Yellow Sea.
-
B.
Seoni
Seoni is a town and district headquarters in the central Indian state of Madhya Pradesh, known for its proximity to Pench National Park and its association with Rudyard Kipling’s "The Jungle Book."
-
C.
Seón
Seón is a variant spelling of the Irish given name Seán, itself equivalent to the English name John.
-
D.
Sansia
Sansia is the former name of Sanxia District, a suburban area in New Taipei City, Taiwan, known for its historic old street and cultural heritage.
-
E.
Tsamai
Tsamai is a Cushitic language spoken by the Tsamai people of southwestern Ethiopia, closely related to other South Omotic languages.
- 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_69da6275fa6c8190952924930adee150 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e674c7296c819092860942de8f28d5 |
completed | April 20, 2026, 6:47 p.m. |
Created at: April 11, 2026, 11:41 p.m.