Triple
T34898854
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Asan Station |
E1006516
|
entity |
| Predicate | connectsLocalServices |
P200135
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Asan Station, connectsLocalServices, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: connectsLocalServices Context triple: [Asan Station, connectsLocalServices, yes]
-
A.
connectsServiceType
Indicates a relationship where one entity is linked or associated to another based on a specific type of service connection.
-
B.
connectsSystem
Indicates that one system establishes a link or interface with another system, enabling interaction or data exchange between them.
-
C.
connectsWorks
Indicates a relationship where one work serves to link, bridge, or associate two or more other works.
-
D.
connectsLocation
Indicates a relationship where one entity serves as a link or route that joins or provides access between two locations.
-
E.
connectsModule
Indicates a relationship where one module is linked or joined to another module to enable interaction or integration between them.
- F. None of above. chosen
Provenance (4 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_69f76dbfe5788190ad8b64f241f470c8 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69ff76ac40988190a34d858b5472ee2b |
completed | May 9, 2026, 6:02 p.m. |
| PD | Predicate disambiguation | batch_69ff760a90948190a12fcb80e6e3e14b |
completed | May 9, 2026, 5:59 p.m. |
| PDg | Predicate description generation | batch_69ff76ab9b4c8190b4cc7c9c733b2765 |
completed | May 9, 2026, 6:02 p.m. |
Created at: May 3, 2026, 4 p.m.