Triple
T24775283
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kaohsiung MRT Red Line |
E619843
|
entity |
| Predicate | otherMainCorridor |
P157721
|
FINISHED |
| Object | Kaohsiung MRT Orange Line |
—
|
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: Kaohsiung MRT Orange Line | Statement: [Kaohsiung MRT Red Line, otherMainCorridor, Kaohsiung MRT Orange Line]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: otherMainCorridor Context triple: [Kaohsiung MRT Red Line, otherMainCorridor, Kaohsiung MRT Orange Line]
-
A.
inCorridor
Indicates that one entity is located within or inside a corridor relative to another spatial context or reference.
-
B.
isMostHeavilyTraveledCorridorIn
Indicates that a particular route or corridor experiences the highest volume of travel or traffic within a specified area or region.
-
C.
hasCorridor
Indicates that one entity includes, is connected by, or provides access through a corridor to another entity.
-
D.
corridorType
Indicates the specific kind or classification of a corridor associated with an entity or location.
-
E.
firstCorridorOpened
Indicates that the first corridor in a sequence or structure has been opened or made accessible.
- 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_69e2fabd04488190a2d13c97be745a2d |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f44a417a58819081777e18dda149fd |
completed | May 1, 2026, 6:37 a.m. |
| PD | Predicate disambiguation | batch_69f442a977b08190b44eac040cb90211 |
completed | May 1, 2026, 6:05 a.m. |
| PDg | Predicate description generation | batch_69f44a3adb7c8190941572f718b3b93c |
completed | May 1, 2026, 6:37 a.m. |
Created at: April 18, 2026, 4:34 a.m.