Triple
T37402810
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | National Rail station code |
E929045
|
entity |
| Predicate | exampleMapping |
P9923
|
FINISHED |
| Object | KGX identifies London King’s Cross |
—
|
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: KGX identifies London King’s Cross | Statement: [National Rail station code, exampleMapping, KGX identifies London King’s Cross]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: exampleMapping Context triple: [National Rail station code, exampleMapping, KGX identifies London King’s Cross]
-
A.
typicalMapping
Indicates a standard or commonly used correspondence between elements of one set, structure, or representation and those of another.
-
B.
mappingBy
Indicates that one entity is related to another through a defined mapping or association, specifying which side or field governs the relationship.
-
C.
mapsTo
chosen
Indicates that one entity is associated with or transformed into another entity, typically defining a directional correspondence or function from a source to a target.
-
D.
mappingSource
Indicates that one entity serves as the origin or provider of a mapping or correspondence that defines how elements relate between two representations or systems.
-
E.
canMap
Indicates that one entity is able to be mapped or transformed systematically into another entity or representation.
- 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_69f76ebbf79c8190b85bbcf3a6be57e4 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fba68077788190b311e027435fcf87 |
completed | May 6, 2026, 8:37 p.m. |
| PD | Predicate disambiguation | batch_69fba34c65ac8190b298f0f00d1dcc0e |
completed | May 6, 2026, 8:23 p.m. |
Created at: May 3, 2026, 4:16 p.m.