Triple
T20133097
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Seoul Subway Line 7 |
E490948
|
entity |
| Predicate | connectsTo |
P845
|
FINISHED |
| Object | EverLine |
—
|
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: EverLine | Statement: [Seoul Subway Line 7, connectsTo, EverLine]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: EverLine Context triple: [Seoul Subway Line 7, connectsTo, EverLine]
-
A.
EverLine
chosen
EverLine is an automated light rail transit line serving the city of Yongin in the Seoul Capital Area, connecting local districts to the broader Seoul Metropolitan Subway network.
-
B.
Evergreen Line
Evergreen Line is a major Taiwanese container shipping company known for operating a large global fleet and extensive international trade routes.
-
C.
City Line
City Line is a residential neighborhood in eastern Brooklyn, New York City, located near the borough’s border with Queens.
-
D.
City Line
City Line is a suburban railway route serving various districts within Cardiff, Wales, as part of the local commuter rail network.
-
E.
City Line
City Line is a commuter rail service on Bangkok’s Suvarnabhumi Airport Rail Link that connects the airport with central city stations using frequent, all-stop trains.
- 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_69da62651a0c8190a3e05e95e056a66b |
completed | April 11, 2026, 3:01 p.m. |
| NER | Named-entity recognition | batch_69e66763ee908190af64af31b4ca2377 |
completed | April 20, 2026, 5:50 p.m. |
Created at: April 11, 2026, 11:32 p.m.