Triple
T25840173
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Incheon Airport Railroad |
E650914
|
entity |
| Predicate | connectsCentralArea |
P97914
|
FINISHED |
| Object | central Seoul |
—
|
LITERAL 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: central Seoul | Statement: [Incheon Airport Railroad, connectsCentralArea, central Seoul]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: connectsCentralArea Context triple: [Incheon Airport Railroad, connectsCentralArea, central Seoul]
-
A.
connectsCentralAreaTo
chosen
Indicates a relationship where one element serves as a link or pathway between a central area and another location or component.
-
B.
connectsArea
Indicates that one area serves as a link or passage between two other areas, enabling movement or interaction between them.
-
C.
connectsAreaNear
Indicates that one entity serves as a link or passage between areas that are geographically close to each other.
-
D.
connectsResidentialArea
Indicates a relationship where something serves as a link or route between one residential area and another.
-
E.
hasAreaConnections
Indicates that an entity is linked to one or more surrounding or related areas, typically representing spatial or regional connections between them.
- F. None of above.
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_69e7ab38086081908f3a8e7e0c6efd83 |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69f6d0d46aec819091edf97324d793ac |
completed | May 3, 2026, 4:36 a.m. |
| PD | Predicate disambiguation | batch_69f6cfe2183481908ae4e85a59c66f69 |
completed | May 3, 2026, 4:32 a.m. |
Created at: April 22, 2026, 7:49 a.m.