Triple
T19768699
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Posco Tower Seoul |
E474824
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Jamsil |
—
|
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: Jamsil | Statement: [Posco Tower Seoul, locatedIn, Jamsil]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jamsil Context triple: [Posco Tower Seoul, locatedIn, Jamsil]
-
A.
Jamsil
chosen
Jamsil is a neighborhood in southeastern Seoul, South Korea, known for its major sports complexes, large residential areas, and entertainment facilities such as Lotte World.
-
B.
Myeong-bok
Myeong-bok is the given name of Gojong, the 26th king of the Joseon dynasty and first emperor of the Korean Empire.
-
C.
Sungneung
Sungneung is a royal Joseon Dynasty tomb located within the Donggureung burial complex in South Korea.
-
D.
Anyangcheon
Anyangcheon is a river in South Korea that flows through the city of Anyang and serves as an important local waterway and recreational area.
-
E.
Yeoncheon
Yeoncheon is a county in Gyeonggi Province, South Korea, known for its location near the Demilitarized Zone (DMZ) and its significant historical and military sites.
- 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_69d8e51a43a08190956bc6df13c91a77 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e65359bb9881908f48282b63a83f2f |
completed | April 20, 2026, 4:24 p.m. |
Created at: April 10, 2026, 1:48 p.m.