Triple
T14890913
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hwaseong Fortress |
E359751
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Suwon |
E401676
|
NE 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: Suwon | Statement: [Hwaseong Fortress, locatedIn, Suwon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Suwon Context triple: [Hwaseong Fortress, locatedIn, Suwon]
-
A.
Suwon
chosen
Suwon is a major South Korean city best known for its UNESCO-listed Hwaseong Fortress and as a key cultural and economic center just south of Seoul.
-
B.
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.
-
C.
Uijeongbu
Uijeongbu is a city in South Korea known as a suburban hub north of Seoul, featuring residential districts, commercial centers, and a history of hosting U.S. military bases.
-
D.
Sangil
Sangil are an indigenous Moro ethnolinguistic group of the southern Philippines and nearby Indonesian islands, known for their seafaring traditions and Islamic faith.
-
E.
Dongducheon
Dongducheon is a city in northern South Korea known for its proximity to the Demilitarized Zone and the presence of U.S. military bases.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d827980cbc8190a0c569ae3940a1d9 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69ded5f883288190af602633fa7d6860 |
completed | April 15, 2026, 12:04 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff3647bda881909a83311926096a29 |
completed | May 9, 2026, 1:27 p.m. |
Created at: April 10, 2026, 2:10 a.m.