Triple
T17870425
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SGL |
E446820
|
entity |
| Predicate | isCodeType |
P2202
|
FINISHED |
| Object | railway station code |
—
|
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: railway station code | Statement: [SGL, isCodeType, railway station code]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isCodeType Context triple: [SGL, isCodeType, railway station code]
-
A.
codeType
chosen
Indicates the classification or category assigned to a particular code within a coding or encoding system.
-
B.
hasTypeCode
Indicates that an entity is associated with a specific type classification represented by a code.
-
C.
isOfficialCodeFor
Indicates that one entity serves as the formally recognized or authorized code that designates or identifies another entity.
-
D.
labelCodeType
Indicates that one entity serves as the type or classification scheme for the labeling code applied to another entity.
-
E.
hasCodeIn
Indicates that one entity is represented, defined, or implemented within the codebase or coding context of another entity.
- 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_69d8b9f4c22c819093c2680434472894 |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e49aa24c8481909de38953a88ff615 |
completed | April 19, 2026, 9:04 a.m. |
| PD | Predicate disambiguation | batch_69e3d8e6d2e88190ad9ef9f8a99f13e6 |
completed | April 18, 2026, 7:17 p.m. |
Created at: April 10, 2026, 10:18 a.m.