Triple
T33471906
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pyeongchon Station |
E857214
|
entity |
| Predicate | connectsCommutersBetween |
P114783
|
FINISHED |
| Object | Anyang |
—
|
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: Anyang | Statement: [Pyeongchon Station, connectsCommutersBetween, Anyang]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: connectsCommutersBetween Context triple: [Pyeongchon Station, connectsCommutersBetween, Anyang]
-
A.
commutesBetween
Indicates a regular pattern of travel back and forth between two locations, typically for work, study, or routine activities.
-
B.
commuterRoute
Indicates a route that is regularly used by people traveling between home and work or other routine daily destinations.
-
C.
operatesCommuterServiceBetween
Indicates that an entity runs a commuter transportation service connecting two specified locations.
-
D.
hasCommuterLinks
chosen
Indicates that there are established transportation connections enabling regular travel between two locations.
-
E.
commuterCorridorFor
Indicates a route or area that serves as a primary pathway for regular travel between two locations, typically used by commuters.
- 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_69f3497472508190b300ebd3fd402367 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69ff1d85441c8190931e758685a269f7 |
completed | May 9, 2026, 11:41 a.m. |
| PD | Predicate disambiguation | batch_69ff1d186cc48190b315c61e23de6551 |
completed | May 9, 2026, 11:40 a.m. |
Created at: May 1, 2026, 1:37 a.m.